{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:15:41.299729Z",
     "start_time": "2020-07-30T13:15:26.941906Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "LC = pd.read_csv('ppdai2017/LC.csv')\n",
    "LP = pd.read_csv('ppdai2017/LP.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:15:43.626418Z",
     "start_time": "2020-07-30T13:15:43.582423Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ListingId</th>\n",
       "      <th>借款金额</th>\n",
       "      <th>借款期限</th>\n",
       "      <th>借款利率</th>\n",
       "      <th>借款成功日期</th>\n",
       "      <th>初始评级</th>\n",
       "      <th>借款类型</th>\n",
       "      <th>是否首标</th>\n",
       "      <th>年龄</th>\n",
       "      <th>性别</th>\n",
       "      <th>...</th>\n",
       "      <th>户口认证</th>\n",
       "      <th>视频认证</th>\n",
       "      <th>学历认证</th>\n",
       "      <th>征信认证</th>\n",
       "      <th>淘宝认证</th>\n",
       "      <th>历史成功借款次数</th>\n",
       "      <th>历史成功借款金额</th>\n",
       "      <th>总待还本金</th>\n",
       "      <th>历史正常还款期数</th>\n",
       "      <th>历史逾期还款期数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>126541</td>\n",
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       "      <td>C</td>\n",
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       "      <td>否</td>\n",
       "      <td>35</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>11</td>\n",
       "      <td>40326.0</td>\n",
       "      <td>8712.73</td>\n",
       "      <td>57</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>133291</td>\n",
       "      <td>9453</td>\n",
       "      <td>12</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2015-03-16</td>\n",
       "      <td>D</td>\n",
       "      <td>其他</td>\n",
       "      <td>否</td>\n",
       "      <td>34</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>4</td>\n",
       "      <td>14500.0</td>\n",
       "      <td>7890.64</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>142421</td>\n",
       "      <td>27000</td>\n",
       "      <td>24</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2016-04-26</td>\n",
       "      <td>E</td>\n",
       "      <td>普通</td>\n",
       "      <td>否</td>\n",
       "      <td>41</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>5</td>\n",
       "      <td>21894.0</td>\n",
       "      <td>11726.32</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>149711</td>\n",
       "      <td>25000</td>\n",
       "      <td>12</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2015-03-30</td>\n",
       "      <td>C</td>\n",
       "      <td>其他</td>\n",
       "      <td>否</td>\n",
       "      <td>34</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>成功认证</td>\n",
       "      <td>成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>6</td>\n",
       "      <td>36190.0</td>\n",
       "      <td>9703.41</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>152141</td>\n",
       "      <td>20000</td>\n",
       "      <td>6</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2015-01-22</td>\n",
       "      <td>C</td>\n",
       "      <td>电商</td>\n",
       "      <td>否</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>成功认证</td>\n",
       "      <td>成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>13</td>\n",
       "      <td>77945.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>118</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别    ...     \\\n",
       "0     126541  18000    12  18.0  2015-05-04    C   其他    否  35  男    ...      \n",
       "1     133291   9453    12  20.0  2015-03-16    D   其他    否  34  男    ...      \n",
       "2     142421  27000    24  20.0  2016-04-26    E   普通    否  41  男    ...      \n",
       "3     149711  25000    12  18.0  2015-03-30    C   其他    否  34  男    ...      \n",
       "4     152141  20000     6  16.0  2015-01-22    C   电商    否  24  男    ...      \n",
       "\n",
       "    户口认证   视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  历史正常还款期数  \\\n",
       "0  未成功认证   成功认证  未成功认证  未成功认证  未成功认证       11   40326.0   8712.73        57   \n",
       "1   成功认证  未成功认证  未成功认证  未成功认证  未成功认证        4   14500.0   7890.64        13   \n",
       "2  未成功认证  未成功认证  未成功认证  未成功认证  未成功认证        5   21894.0  11726.32        25   \n",
       "3   成功认证   成功认证  未成功认证  未成功认证  未成功认证        6   36190.0   9703.41        41   \n",
       "4   成功认证   成功认证  未成功认证  未成功认证  未成功认证       13   77945.0      0.00       118   \n",
       "\n",
       "   历史逾期还款期数  \n",
       "0        16  \n",
       "1         1  \n",
       "2         3  \n",
       "3         1  \n",
       "4        14  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LC.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:15:45.993040Z",
     "start_time": "2020-07-30T13:15:45.964059Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>ListingId</th>\n",
       "      <th>期数</th>\n",
       "      <th>还款状态</th>\n",
       "      <th>应还本金</th>\n",
       "      <th>应还利息</th>\n",
       "      <th>剩余本金</th>\n",
       "      <th>剩余利息</th>\n",
       "      <th>到期日期</th>\n",
       "      <th>还款日期</th>\n",
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       "  <tbody>\n",
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       "      <td>126541</td>\n",
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       "      <td>270.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-06-04</td>\n",
       "      <td>2015-06-04</td>\n",
       "      <td>2017-02-22</td>\n",
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       "      <td>126541</td>\n",
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       "      <td>1400.94</td>\n",
       "      <td>249.29</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>2015-07-04</td>\n",
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       "      <td>126541</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-08-04</td>\n",
       "      <td>2015-08-04</td>\n",
       "      <td>2017-02-22</td>\n",
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       "      <td>126541</td>\n",
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       "      <td>1</td>\n",
       "      <td>1443.28</td>\n",
       "      <td>206.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-09-04</td>\n",
       "      <td>2015-09-04</td>\n",
       "      <td>2017-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>126541</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1464.93</td>\n",
       "      <td>185.30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-10-04</td>\n",
       "      <td>2015-10-04</td>\n",
       "      <td>2017-02-22</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ListingId  期数  还款状态     应还本金    应还利息  剩余本金  剩余利息        到期日期        还款日期  \\\n",
       "0     126541   1     1  1380.23  270.00   0.0   0.0  2015-06-04  2015-06-04   \n",
       "1     126541   2     1  1400.94  249.29   0.0   0.0  2015-07-04  2015-07-04   \n",
       "2     126541   3     1  1421.95  228.28   0.0   0.0  2015-08-04  2015-08-04   \n",
       "3     126541   4     1  1443.28  206.95   0.0   0.0  2015-09-04  2015-09-04   \n",
       "4     126541   5     1  1464.93  185.30   0.0   0.0  2015-10-04  2015-10-04   \n",
       "\n",
       "   recorddate  \n",
       "0  2017-02-22  \n",
       "1  2017-02-22  \n",
       "2  2017-02-22  \n",
       "3  2017-02-22  \n",
       "4  2017-02-22  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LP.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 对数据进行清洗\n",
    "* 一次检查重复值/缺失值的处理,一致化以及异常值,数据集很干净"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:26.205366Z",
     "start_time": "2020-07-30T13:36:25.886550Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 328553 entries, 0 to 328552\n",
      "Data columns (total 22 columns):\n",
      "ListingId    328553 non-null int64\n",
      "借款金额         328553 non-null int64\n",
      "借款期限         328553 non-null int64\n",
      "借款利率         328553 non-null float64\n",
      "借款成功日期       328553 non-null object\n",
      "初始评级         328553 non-null object\n",
      "借款类型         328553 non-null object\n",
      "是否首标         328553 non-null object\n",
      "年龄           328553 non-null int64\n",
      "性别           328553 non-null object\n",
      "手机认证         328553 non-null object\n",
      "户口认证         328553 non-null object\n",
      "视频认证         328553 non-null object\n",
      "学历认证         328553 non-null object\n",
      "征信认证         328553 non-null object\n",
      "淘宝认证         328553 non-null object\n",
      "历史成功借款次数     328553 non-null int64\n",
      "历史成功借款金额     328553 non-null float64\n",
      "总待还本金        328553 non-null float64\n",
      "历史正常还款期数     328553 non-null int64\n",
      "历史逾期还款期数     328553 non-null int64\n",
      "逾期还款率        239602 non-null float64\n",
      "dtypes: float64(4), int64(7), object(11)\n",
      "memory usage: 57.7+ MB\n"
     ]
    }
   ],
   "source": [
    "LC['逾期还款率'] = LC['历史逾期还款期数']/(LC['历史逾期还款期数']+LC['历史正常还款期数'])*100\n",
    "LC.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:31.639459Z",
     "start_time": "2020-07-30T13:36:31.326640Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 328553 entries, 0 to 328552\n",
      "Data columns (total 22 columns):\n",
      "ListingId    328553 non-null int64\n",
      "借款金额         328553 non-null int64\n",
      "借款期限         328553 non-null int64\n",
      "借款利率         328553 non-null float64\n",
      "借款成功日期       328553 non-null object\n",
      "初始评级         328553 non-null object\n",
      "借款类型         328553 non-null object\n",
      "是否首标         328553 non-null object\n",
      "年龄           328553 non-null int64\n",
      "性别           328553 non-null object\n",
      "手机认证         328553 non-null object\n",
      "户口认证         328553 non-null object\n",
      "视频认证         328553 non-null object\n",
      "学历认证         328553 non-null object\n",
      "征信认证         328553 non-null object\n",
      "淘宝认证         328553 non-null object\n",
      "历史成功借款次数     328553 non-null int64\n",
      "历史成功借款金额     328553 non-null float64\n",
      "总待还本金        328553 non-null float64\n",
      "历史正常还款期数     328553 non-null int64\n",
      "历史逾期还款期数     328553 non-null int64\n",
      "逾期还款率        239602 non-null float64\n",
      "dtypes: float64(4), int64(7), object(11)\n",
      "memory usage: 57.7+ MB\n"
     ]
    }
   ],
   "source": [
    "LC.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:34.362896Z",
     "start_time": "2020-07-30T13:36:34.018094Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
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       "      <th>ListingId</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>1.907948e+07</td>\n",
       "      <td>8.375769e+06</td>\n",
       "      <td>126541.0</td>\n",
       "      <td>11908871.0</td>\n",
       "      <td>19523251.00</td>\n",
       "      <td>26298621.00</td>\n",
       "      <td>32819531.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>借款金额</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>4.423817e+03</td>\n",
       "      <td>1.121966e+04</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2033.0</td>\n",
       "      <td>3397.00</td>\n",
       "      <td>5230.00</td>\n",
       "      <td>500000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>借款期限</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>1.021359e+01</td>\n",
       "      <td>2.780444e+00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>24.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>借款利率</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>2.060144e+01</td>\n",
       "      <td>1.772408e+00</td>\n",
       "      <td>6.5</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>22.00</td>\n",
       "      <td>24.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年龄</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>2.914304e+01</td>\n",
       "      <td>6.624286e+00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>28.00</td>\n",
       "      <td>33.00</td>\n",
       "      <td>56.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史成功借款次数</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>2.323159e+00</td>\n",
       "      <td>2.922361e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>649.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史成功借款金额</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>8.785857e+03</td>\n",
       "      <td>3.502736e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5000.00</td>\n",
       "      <td>10355.00</td>\n",
       "      <td>7405926.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总待还本金</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>3.721665e+03</td>\n",
       "      <td>8.626061e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2542.41</td>\n",
       "      <td>5446.81</td>\n",
       "      <td>1172652.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史正常还款期数</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>9.947658e+00</td>\n",
       "      <td>1.483990e+01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>13.00</td>\n",
       "      <td>2507.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史逾期还款期数</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>4.232498e-01</td>\n",
       "      <td>1.595681e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>60.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>逾期还款率</th>\n",
       "      <td>239602.0</td>\n",
       "      <td>3.907802e+00</td>\n",
       "      <td>1.080683e+01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              count          mean           std       min         25%  \\\n",
       "ListingId  328553.0  1.907948e+07  8.375769e+06  126541.0  11908871.0   \n",
       "借款金额       328553.0  4.423817e+03  1.121966e+04     100.0      2033.0   \n",
       "借款期限       328553.0  1.021359e+01  2.780444e+00       1.0         6.0   \n",
       "借款利率       328553.0  2.060144e+01  1.772408e+00       6.5        20.0   \n",
       "年龄         328553.0  2.914304e+01  6.624286e+00      17.0        24.0   \n",
       "历史成功借款次数   328553.0  2.323159e+00  2.922361e+00       0.0         0.0   \n",
       "历史成功借款金额   328553.0  8.785857e+03  3.502736e+04       0.0         0.0   \n",
       "总待还本金      328553.0  3.721665e+03  8.626061e+03       0.0         0.0   \n",
       "历史正常还款期数   328553.0  9.947658e+00  1.483990e+01       0.0         0.0   \n",
       "历史逾期还款期数   328553.0  4.232498e-01  1.595681e+00       0.0         0.0   \n",
       "逾期还款率      239602.0  3.907802e+00  1.080683e+01       0.0         0.0   \n",
       "\n",
       "                   50%          75%          max  \n",
       "ListingId  19523251.00  26298621.00  32819531.00  \n",
       "借款金额           3397.00      5230.00    500000.00  \n",
       "借款期限             12.00        12.00        24.00  \n",
       "借款利率             20.00        22.00        24.00  \n",
       "年龄               28.00        33.00        56.00  \n",
       "历史成功借款次数          2.00         3.00       649.00  \n",
       "历史成功借款金额       5000.00     10355.00   7405926.00  \n",
       "总待还本金          2542.41      5446.81   1172652.87  \n",
       "历史正常还款期数          5.00        13.00      2507.00  \n",
       "历史逾期还款期数          0.00         0.00        60.00  \n",
       "逾期还款率             0.00         0.00       100.00  "
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LC.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:36.731538Z",
     "start_time": "2020-07-30T13:36:36.642590Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "20799011    1\n",
       "Name: ListingId, Length: 328553, dtype: int64"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LC['ListingId'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:39.131162Z",
     "start_time": "2020-07-30T13:36:39.118172Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 3203276 entries, 0 to 3203275\n",
      "Data columns (total 10 columns):\n",
      "ListingId     int64\n",
      "期数            int64\n",
      "还款状态          int64\n",
      "应还本金          float64\n",
      "应还利息          float64\n",
      "剩余本金          float64\n",
      "剩余利息          float64\n",
      "到期日期          object\n",
      "还款日期          object\n",
      "recorddate    object\n",
      "dtypes: float64(4), int64(3), object(3)\n",
      "memory usage: 268.8+ MB\n"
     ]
    }
   ],
   "source": [
    "LP.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:41.857598Z",
     "start_time": "2020-07-30T13:36:41.527788Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ListingId</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>1.907948e+07</td>\n",
       "      <td>8.375769e+06</td>\n",
       "      <td>126541.0</td>\n",
       "      <td>11908871.0</td>\n",
       "      <td>19523251.00</td>\n",
       "      <td>26298621.00</td>\n",
       "      <td>32819531.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>借款金额</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>4.423817e+03</td>\n",
       "      <td>1.121966e+04</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2033.0</td>\n",
       "      <td>3397.00</td>\n",
       "      <td>5230.00</td>\n",
       "      <td>500000.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>借款期限</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>1.021359e+01</td>\n",
       "      <td>2.780444e+00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>24.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>借款利率</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>2.060144e+01</td>\n",
       "      <td>1.772408e+00</td>\n",
       "      <td>6.5</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>22.00</td>\n",
       "      <td>24.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年龄</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>2.914304e+01</td>\n",
       "      <td>6.624286e+00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>28.00</td>\n",
       "      <td>33.00</td>\n",
       "      <td>56.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史成功借款次数</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>2.323159e+00</td>\n",
       "      <td>2.922361e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>649.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史成功借款金额</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>8.785857e+03</td>\n",
       "      <td>3.502736e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5000.00</td>\n",
       "      <td>10355.00</td>\n",
       "      <td>7405926.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总待还本金</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>3.721665e+03</td>\n",
       "      <td>8.626061e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2542.41</td>\n",
       "      <td>5446.81</td>\n",
       "      <td>1172652.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史正常还款期数</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>9.947658e+00</td>\n",
       "      <td>1.483990e+01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>13.00</td>\n",
       "      <td>2507.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>历史逾期还款期数</th>\n",
       "      <td>328553.0</td>\n",
       "      <td>4.232498e-01</td>\n",
       "      <td>1.595681e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>60.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>逾期还款率</th>\n",
       "      <td>239602.0</td>\n",
       "      <td>3.907802e+00</td>\n",
       "      <td>1.080683e+01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              count          mean           std       min         25%  \\\n",
       "ListingId  328553.0  1.907948e+07  8.375769e+06  126541.0  11908871.0   \n",
       "借款金额       328553.0  4.423817e+03  1.121966e+04     100.0      2033.0   \n",
       "借款期限       328553.0  1.021359e+01  2.780444e+00       1.0         6.0   \n",
       "借款利率       328553.0  2.060144e+01  1.772408e+00       6.5        20.0   \n",
       "年龄         328553.0  2.914304e+01  6.624286e+00      17.0        24.0   \n",
       "历史成功借款次数   328553.0  2.323159e+00  2.922361e+00       0.0         0.0   \n",
       "历史成功借款金额   328553.0  8.785857e+03  3.502736e+04       0.0         0.0   \n",
       "总待还本金      328553.0  3.721665e+03  8.626061e+03       0.0         0.0   \n",
       "历史正常还款期数   328553.0  9.947658e+00  1.483990e+01       0.0         0.0   \n",
       "历史逾期还款期数   328553.0  4.232498e-01  1.595681e+00       0.0         0.0   \n",
       "逾期还款率      239602.0  3.907802e+00  1.080683e+01       0.0         0.0   \n",
       "\n",
       "                   50%          75%          max  \n",
       "ListingId  19523251.00  26298621.00  32819531.00  \n",
       "借款金额           3397.00      5230.00    500000.00  \n",
       "借款期限             12.00        12.00        24.00  \n",
       "借款利率             20.00        22.00        24.00  \n",
       "年龄               28.00        33.00        56.00  \n",
       "历史成功借款次数          2.00         3.00       649.00  \n",
       "历史成功借款金额       5000.00     10355.00   7405926.00  \n",
       "总待还本金          2542.41      5446.81   1172652.87  \n",
       "历史正常还款期数          5.00        13.00      2507.00  \n",
       "历史逾期还款期数          0.00         0.00        60.00  \n",
       "逾期还款率             0.00         0.00       100.00  "
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LC.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:45.706604Z",
     "start_time": "2020-07-30T13:36:44.219457Z"
    }
   },
   "outputs": [],
   "source": [
    "LP=LP.dropna(how='any')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:48.021278Z",
     "start_time": "2020-07-30T13:36:48.009284Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 3203276 entries, 0 to 3203275\n",
      "Data columns (total 10 columns):\n",
      "ListingId     int64\n",
      "期数            int64\n",
      "还款状态          int64\n",
      "应还本金          float64\n",
      "应还利息          float64\n",
      "剩余本金          float64\n",
      "剩余利息          float64\n",
      "到期日期          object\n",
      "还款日期          object\n",
      "recorddate    object\n",
      "dtypes: float64(4), int64(3), object(3)\n",
      "memory usage: 268.8+ MB\n"
     ]
    }
   ],
   "source": [
    "LP.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:51.861864Z",
     "start_time": "2020-07-30T13:36:51.487924Z"
    }
   },
   "outputs": [],
   "source": [
    "LC=LC.dropna(how='any')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:36:54.334430Z",
     "start_time": "2020-07-30T13:36:54.101562Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 239602 entries, 0 to 328552\n",
      "Data columns (total 22 columns):\n",
      "ListingId    239602 non-null int64\n",
      "借款金额         239602 non-null int64\n",
      "借款期限         239602 non-null int64\n",
      "借款利率         239602 non-null float64\n",
      "借款成功日期       239602 non-null object\n",
      "初始评级         239602 non-null object\n",
      "借款类型         239602 non-null object\n",
      "是否首标         239602 non-null object\n",
      "年龄           239602 non-null int64\n",
      "性别           239602 non-null object\n",
      "手机认证         239602 non-null object\n",
      "户口认证         239602 non-null object\n",
      "视频认证         239602 non-null object\n",
      "学历认证         239602 non-null object\n",
      "征信认证         239602 non-null object\n",
      "淘宝认证         239602 non-null object\n",
      "历史成功借款次数     239602 non-null int64\n",
      "历史成功借款金额     239602 non-null float64\n",
      "总待还本金        239602 non-null float64\n",
      "历史正常还款期数     239602 non-null int64\n",
      "历史逾期还款期数     239602 non-null int64\n",
      "逾期还款率        239602 non-null float64\n",
      "dtypes: float64(4), int64(7), object(11)\n",
      "memory usage: 42.0+ MB\n"
     ]
    }
   ],
   "source": [
    "LC.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:35:47.336655Z",
     "start_time": "2020-07-30T13:35:46.977861Z"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.分析用户画像（性别、学历、年龄、是否首标）\n",
    "\n",
    "* 按‘性别’、‘年龄’、‘是否首标’、‘学历认证’字段对‘借款金额’进行加总，用饼图或柱状图将结果可视化\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 性别分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:06.698045Z",
     "start_time": "2020-07-30T13:37:06.364240Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(        ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "0          126541  18000    12  18.0  2015-05-04    C     其他    否  35  男   \n",
      "1          133291   9453    12  20.0  2015-03-16    D     其他    否  34  男   \n",
      "2          142421  27000    24  20.0  2016-04-26    E     普通    否  41  男   \n",
      "3          149711  25000    12  18.0  2015-03-30    C     其他    否  34  男   \n",
      "4          152141  20000     6  16.0  2015-01-22    C     电商    否  24  男   \n",
      "5          162641  20000    12  14.0  2015-03-25    A     普通    否  36  男   \n",
      "7          175451  20000    12  18.0  2016-03-19    B     普通    否  32  男   \n",
      "9          193831  10475     6  18.0  2015-04-15    C     电商    否  25  男   \n",
      "10         199461  25000    12  20.0  2015-11-29    E     普通    否  29  男   \n",
      "11         209191  20000    12  20.0  2015-11-28    E     普通    否  33  男   \n",
      "12         209381  30000    24  16.0  2015-06-28    E     其他    否  30  男   \n",
      "13         223081  26000    12  20.0  2016-06-28    E     普通    否  35  男   \n",
      "14         528911  11000    12  20.0  2015-03-10    C     其他    否  47  男   \n",
      "15        1080421   5250     6  18.0  2015-05-27    C     电商    否  25  男   \n",
      "16        1518801   4913    12  24.0  2015-01-01    D     普通    否  26  男   \n",
      "19        1537191   3228    12  24.0  2015-01-02    F     普通    否  39  男   \n",
      "20        1537391   5161    12  24.0  2015-01-02    F     普通    否  35  男   \n",
      "21        1537661   8000    12  20.0  2015-01-04    C     普通    否  39  男   \n",
      "23        1540111  12778    12  20.0  2015-01-04    D     普通    否  26  男   \n",
      "24        1541631  10000    12  20.0  2015-01-04    D     普通    否  38  男   \n",
      "25        1541641  11578    12  20.0  2015-01-04    D     其他    否  27  男   \n",
      "26        1541761  10000    12  20.0  2015-01-04    D     普通    否  29  男   \n",
      "27        1542581   3500    12  18.0  2015-01-04    C     普通    否  28  男   \n",
      "28        1542681  13083    12  18.0  2015-01-04    C     普通    否  46  男   \n",
      "30        1546771  12000    12  18.0  2015-01-04    C     普通    否  27  男   \n",
      "31        1547751   3900    12  23.0  2015-01-04    E     普通    否  27  男   \n",
      "32        1548231   8000    12  20.0  2015-01-04    D     其他    否  27  男   \n",
      "33        1548521  10053    12  18.0  2015-01-07    C     普通    否  34  男   \n",
      "35        1549891   4940    12  22.0  2015-01-02    C     普通    否  24  男   \n",
      "36        1550751   3500    12  20.0  2015-01-05    D     普通    否  27  男   \n",
      "...           ...    ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328510   32815471   2571    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328511   32815751    990    12  22.0  2017-01-30    D  APP闪电    否  36  男   \n",
      "328512   32815861   4000    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328513   32815871   3327    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328516   32816401   3548    12  20.0  2017-01-30    D     普通    否  38  男   \n",
      "328517   32816441   2500    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328518   32816561   2431    12  22.0  2017-01-30    D     其他    否  43  男   \n",
      "328519   32816991   2000     6  20.0  2017-01-30    D     其他    否  35  男   \n",
      "328523   32817151   4564     6  20.0  2017-01-30    C     其他    否  30  男   \n",
      "328524   32817221   5100    12  20.0  2017-01-30    B     普通    否  24  男   \n",
      "328526   32817361   7354    12  20.0  2017-01-30    C     普通    否  25  男   \n",
      "328527   32817401   1200    12  20.0  2017-01-30    C  APP闪电    否  22  男   \n",
      "328530   32817701   1041    12  20.0  2017-01-30    C     普通    否  24  男   \n",
      "328534   32818011    728    12  20.0  2017-01-30    C  APP闪电    否  36  男   \n",
      "328536   32818051   1175    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328537   32818161   2873     6  16.0  2017-01-30    C     普通    否  28  男   \n",
      "328538   32818171   1677    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328539   32818231   2256     6  20.0  2017-01-30    C     其他    否  39  男   \n",
      "328540   32818411   1814    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328541   32818591   2067    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328542   32818621   3500     6  20.0  2017-01-30    C     其他    否  34  男   \n",
      "328543   32818851   5804    12  20.0  2017-01-30    C     其他    否  44  男   \n",
      "328544   32818871   6880     6  20.0  2017-01-30    C     其他    否  28  男   \n",
      "328545   32818901   5008    12  20.0  2017-01-30    C     其他    否  28  男   \n",
      "328546   32818911    782    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "328547   32818941   2200    12  22.0  2017-01-30    D     其他    否  32  男   \n",
      "328548   32819271   2389     6  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328549   32819381   7000    12  20.0  2017-01-30    C     其他    否  22  男   \n",
      "328551   32819511   6406    12  20.0  2017-01-30    C     其他    否  33  男   \n",
      "328552   32819531   3440    12  22.0  2017-01-30    D     其他    否  27  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  \\\n",
      "0         ...       成功认证  未成功认证  未成功认证  未成功认证       11   40326.0   8712.73   \n",
      "1         ...      未成功认证  未成功认证  未成功认证  未成功认证        4   14500.0   7890.64   \n",
      "2         ...      未成功认证  未成功认证  未成功认证  未成功认证        5   21894.0  11726.32   \n",
      "3         ...       成功认证  未成功认证  未成功认证  未成功认证        6   36190.0   9703.41   \n",
      "4         ...       成功认证  未成功认证  未成功认证  未成功认证       13   77945.0      0.00   \n",
      "5         ...       成功认证  未成功认证  未成功认证  未成功认证        7   35622.0      0.00   \n",
      "7         ...       成功认证  未成功认证  未成功认证  未成功认证        7   35000.0   4078.61   \n",
      "9         ...       成功认证  未成功认证  未成功认证  未成功认证        9  107000.0      0.00   \n",
      "10        ...       成功认证  未成功认证  未成功认证  未成功认证       12   71701.0   8109.78   \n",
      "11        ...       成功认证  未成功认证  未成功认证  未成功认证       12   79566.0      0.00   \n",
      "12        ...       成功认证  未成功认证  未成功认证  未成功认证        7   39000.0      0.00   \n",
      "13        ...       成功认证  未成功认证   成功认证  未成功认证       12   54122.0   8388.58   \n",
      "14        ...      未成功认证  未成功认证  未成功认证  未成功认证        5   17809.0   3589.14   \n",
      "15        ...       成功认证  未成功认证  未成功认证   成功认证        7  379000.0  10745.88   \n",
      "16        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "19        ...      未成功认证  未成功认证  未成功认证  未成功认证        7   31100.0   7942.98   \n",
      "20        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10128.0   3284.98   \n",
      "21        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "23        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   12700.0   1703.56   \n",
      "24        ...       成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "25        ...       成功认证  未成功认证  未成功认证  未成功认证        4   20366.0   8378.53   \n",
      "26        ...      未成功认证   成功认证  未成功认证  未成功认证        3    9500.0   5452.42   \n",
      "27        ...       成功认证  未成功认证  未成功认证  未成功认证        3    9399.0   3130.15   \n",
      "28        ...       成功认证   成功认证  未成功认证  未成功认证        5   22100.0   6015.72   \n",
      "30        ...      未成功认证   成功认证  未成功认证  未成功认证        6   23000.0   7633.48   \n",
      "31        ...       成功认证  未成功认证  未成功认证  未成功认证        2    6200.0   1651.70   \n",
      "32        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "33        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10000.0   4393.83   \n",
      "35        ...       成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "36        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10500.0   6078.40   \n",
      "...       ...        ...    ...    ...    ...      ...       ...       ...   \n",
      "328510    ...      未成功认证  未成功认证  未成功认证  未成功认证       10   16548.0   6328.08   \n",
      "328511    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1500.0    509.15   \n",
      "328512    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    4000.0      0.00   \n",
      "328513    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1000.0    672.73   \n",
      "328516    ...      未成功认证  未成功认证  未成功认证  未成功认证        5   22360.0  11877.89   \n",
      "328517    ...      未成功认证   成功认证  未成功认证  未成功认证        3    2000.0   1438.58   \n",
      "328518    ...      未成功认证  未成功认证  未成功认证  未成功认证        5   19842.0   8068.86   \n",
      "328519    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    8000.0   4982.88   \n",
      "328523    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3200.0   2435.46   \n",
      "328524    ...      未成功认证   成功认证  未成功认证  未成功认证        2    6164.0   4301.54   \n",
      "328526    ...      未成功认证   成功认证  未成功认证  未成功认证        6   30639.0  10175.77   \n",
      "328527    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1750.0    603.74   \n",
      "328530    ...       成功认证  未成功认证  未成功认证  未成功认证        4    4415.0   3058.81   \n",
      "328534    ...      未成功认证   成功认证  未成功认证  未成功认证        7   10948.0   6271.30   \n",
      "328536    ...       成功认证  未成功认证  未成功认证  未成功认证        1    4500.0   3424.88   \n",
      "328537    ...       成功认证   成功认证   成功认证  未成功认证        9   33377.0  18207.50   \n",
      "328538    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    4805.0   2422.66   \n",
      "328539    ...      未成功认证   成功认证  未成功认证  未成功认证        6   27142.0  15743.41   \n",
      "328540    ...      未成功认证   成功认证  未成功认证  未成功认证        2    5000.0   2885.30   \n",
      "328541    ...      未成功认证   成功认证  未成功认证  未成功认证        2    3993.0   3332.43   \n",
      "328542    ...      未成功认证   成功认证  未成功认证  未成功认证        7   26502.0   6916.73   \n",
      "328543    ...      未成功认证   成功认证  未成功认证  未成功认证        3   12421.0   5395.26   \n",
      "328544    ...      未成功认证   成功认证  未成功认证  未成功认证        5   19208.0  16184.84   \n",
      "328545    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   10500.0   7727.37   \n",
      "328546    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    4818.0   3217.74   \n",
      "328547    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    7200.0   1154.51   \n",
      "328548    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   10000.0   7610.82   \n",
      "328549    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2100.0      0.00   \n",
      "328551    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3500.0   1593.59   \n",
      "328552    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    4500.0   3059.31   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "0             57        16  21.917808  \n",
      "1             13         1   7.142857  \n",
      "2             25         3  10.714286  \n",
      "3             41         1   2.380952  \n",
      "4            118        14  10.606061  \n",
      "5             56         0   0.000000  \n",
      "7             52         0   0.000000  \n",
      "9             49         4   7.547170  \n",
      "10            82         0   0.000000  \n",
      "11            82         0   0.000000  \n",
      "12            27         1   3.571429  \n",
      "13            34         0   0.000000  \n",
      "14            25         2   7.407407  \n",
      "15            31         2   6.060606  \n",
      "16             2         0   0.000000  \n",
      "19            12         9  42.857143  \n",
      "20            17         9  34.615385  \n",
      "21             1         0   0.000000  \n",
      "23            19         0   0.000000  \n",
      "24             6         1  14.285714  \n",
      "25             9         0   0.000000  \n",
      "26             5         2  28.571429  \n",
      "27            10         0   0.000000  \n",
      "28            19         0   0.000000  \n",
      "30            34         4  10.526316  \n",
      "31             8         5  38.461538  \n",
      "32             7         0   0.000000  \n",
      "33            12         0   0.000000  \n",
      "35             4         0   0.000000  \n",
      "36            13         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "328510        45         0   0.000000  \n",
      "328511         3         1  25.000000  \n",
      "328512         6         0   0.000000  \n",
      "328513         2         0   0.000000  \n",
      "328516        24         0   0.000000  \n",
      "328517         8         0   0.000000  \n",
      "328518        21        10  32.258065  \n",
      "328519        13         0   0.000000  \n",
      "328523         3         0   0.000000  \n",
      "328524         5         3  37.500000  \n",
      "328526        33         5  13.157895  \n",
      "328527         8         0   0.000000  \n",
      "328530        16         0   0.000000  \n",
      "328534        28         0   0.000000  \n",
      "328536         3         0   0.000000  \n",
      "328537        26         1   3.703704  \n",
      "328538        10         0   0.000000  \n",
      "328539        24         0   0.000000  \n",
      "328540         7         0   0.000000  \n",
      "328541         4         0   0.000000  \n",
      "328542        45         0   0.000000  \n",
      "328543        15         1   6.250000  \n",
      "328544         9         2  18.181818  \n",
      "328545        14         0   0.000000  \n",
      "328546         4         1  20.000000  \n",
      "328547        15         3  16.666667  \n",
      "328548         3         0   0.000000  \n",
      "328549        12         0   0.000000  \n",
      "328551         7         0   0.000000  \n",
      "328552         4         0   0.000000  \n",
      "\n",
      "[164411 rows x 22 columns],         ListingId    借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "6          171191    3940     6  18.0  2015-06-26    E     电商    否  27  女   \n",
      "8          182261   25000    12  16.0  2015-03-21    B     其他    否  33  女   \n",
      "18        1536991    3885    12  24.0  2015-01-04    F     普通    否  47  女   \n",
      "22        1538211    3000    12  20.0  2015-01-04    D     普通    否  23  女   \n",
      "29        1542821   11748    12  18.0  2015-01-04    C     普通    否  29  女   \n",
      "41        1551961    8972    12  18.0  2015-01-06    C     普通    否  31  女   \n",
      "43        1553501  400000     6  14.0  2015-01-03    B     电商    否  44  女   \n",
      "45        1555121    3158    12  20.0  2015-01-07    D     普通    否  23  女   \n",
      "48        1557241    9243    12  18.0  2015-01-07    C     其他    否  28  女   \n",
      "49        1558081   10000    12  18.0  2015-01-07    C     普通    否  30  女   \n",
      "55        1560101   10000    12  16.0  2015-01-07    C     普通    否  34  女   \n",
      "78        1578731    4260    10  18.0  2015-01-07    C     普通    否  26  女   \n",
      "80        1579171   10000    12  18.0  2015-01-07    B     普通    否  40  女   \n",
      "81        1579591    4311    10  20.0  2015-01-04    C     电商    否  27  女   \n",
      "105       1588621    5662    12  18.0  2015-01-09    C     普通    否  24  女   \n",
      "106       1589451    8109    12  22.0  2015-01-07    E     普通    否  31  女   \n",
      "108       1590361    4284    12  20.0  2015-01-07    D     普通    否  31  女   \n",
      "110       1592201    5000     6  14.0  2015-01-04    A     普通    否  32  女   \n",
      "134       1604901   60000    12  18.0  2015-01-05    D     普通    否  35  女   \n",
      "164       1615891   10000    12  18.0  2015-01-21    C     普通    否  25  女   \n",
      "166       1616741    6020    12  20.0  2015-01-10    D     普通    否  22  女   \n",
      "169       1621581    3070     6  20.0  2015-01-06    B     普通    否  26  女   \n",
      "170       1621661    4601    12  22.0  2015-01-07    D     普通    否  24  女   \n",
      "172       1622451    3009    12  22.0  2015-01-07    E     普通    否  25  女   \n",
      "186       1628811   10000    12  22.0  2015-01-13    D     其他    否  27  女   \n",
      "187       1629111    4420     6  16.0  2015-01-07    C     电商    否  25  女   \n",
      "204       1633201    3500    12  20.0  2015-01-11    D     普通    否  32  女   \n",
      "205       1634121    5731    12  20.0  2015-01-20    D     普通    否  50  女   \n",
      "208       1636071   10773    12  20.0  2015-01-15    D     其他    否  41  女   \n",
      "218       1642141   18000    12  16.0  2015-01-09    B     其他    否  31  女   \n",
      "...           ...     ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328435   32809711    3572     6  18.0  2017-01-30    B  APP闪电    否  26  女   \n",
      "328437   32809801    5000     8  20.0  2017-01-30    C     其他    否  27  女   \n",
      "328448   32810631    3000    10  20.0  2017-01-30    C     其他    否  30  女   \n",
      "328453   32810861    2109     6  20.0  2017-01-30    C     其他    否  24  女   \n",
      "328454   32810981    5630     6  20.0  2017-01-30    C     普通    否  34  女   \n",
      "328459   32811371    3633    11  20.0  2017-01-30    C     其他    否  22  女   \n",
      "328464   32811881    9500     9  20.0  2017-01-30    C     其他    否  33  女   \n",
      "328465   32811921    1000    12  18.0  2017-01-30    B  APP闪电    否  19  女   \n",
      "328466   32811931    4202     9  20.0  2017-01-30    C     普通    否  33  女   \n",
      "328468   32812091    2200    12  22.0  2017-01-30    D  APP闪电    否  26  女   \n",
      "328485   32813391     700    12  20.0  2017-01-30    C  APP闪电    否  23  女   \n",
      "328486   32813431    2026     6  20.0  2017-01-30    C     其他    否  29  女   \n",
      "328491   32814011    2320     6  16.0  2017-01-30    A     其他    否  31  女   \n",
      "328494   32814141     995    12  18.0  2017-01-30    B  APP闪电    否  35  女   \n",
      "328497   32814351    5000     6  20.0  2017-01-30    C     其他    否  39  女   \n",
      "328499   32814611    2119     6  20.0  2017-01-30    D     其他    否  40  女   \n",
      "328501   32814781    1556     6  18.0  2017-01-30    B  APP闪电    否  29  女   \n",
      "328502   32814971    2354    12  16.0  2017-01-30    C     其他    否  23  女   \n",
      "328507   32815401    4497    12  22.0  2017-01-30    C     其他    否  38  女   \n",
      "328515   32816321     700    12  22.0  2017-01-30    D  APP闪电    否  22  女   \n",
      "328520   32817051    2351     6  20.0  2017-01-30    C     其他    否  53  女   \n",
      "328522   32817131    3592    12  22.0  2017-01-30    D  APP闪电    否  31  女   \n",
      "328525   32817231    2365    12  18.0  2017-01-30    B     其他    否  28  女   \n",
      "328528   32817451    2000     6  18.0  2017-01-30    C     其他    否  27  女   \n",
      "328529   32817621    5000    12  18.0  2017-01-30    B     其他    否  24  女   \n",
      "328531   32817811     730    12  22.0  2017-01-30    D  APP闪电    否  30  女   \n",
      "328532   32817821    2807    12  22.0  2017-01-30    D     其他    否  38  女   \n",
      "328533   32817951    2000    12  20.0  2017-01-30    C     普通    否  26  女   \n",
      "328535   32818041     782     6  20.0  2017-01-30    C  APP闪电    否  38  女   \n",
      "328550   32819451    2017     6  20.0  2017-01-30    C     其他    否  36  女   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  \\\n",
      "6         ...       成功认证  未成功认证  未成功认证  未成功认证       15   63989.0   6619.37   \n",
      "8         ...       成功认证  未成功认证  未成功认证  未成功认证        7   42530.0   7418.35   \n",
      "18        ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6200.0   3827.98   \n",
      "22        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   1043.36   \n",
      "29        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12000.0   6766.82   \n",
      "41        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12200.0   4796.70   \n",
      "43        ...       成功认证  未成功认证  未成功认证  未成功认证        1  350000.0      0.00   \n",
      "45        ...       成功认证  未成功认证  未成功认证  未成功认证        2    6300.0   1454.93   \n",
      "48        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10000.0   4430.56   \n",
      "49        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   21000.0   5041.21   \n",
      "55        ...      未成功认证  未成功认证  未成功认证  未成功认证        3    9741.0   5642.67   \n",
      "78        ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0   1739.84   \n",
      "80        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10328.0   3108.53   \n",
      "81        ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6147.0   3012.83   \n",
      "105       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0    880.34   \n",
      "106       ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6200.0      0.00   \n",
      "108       ...      未成功认证  未成功认证  未成功认证  未成功认证        3    9499.0   5747.85   \n",
      "110       ...       成功认证   成功认证  未成功认证  未成功认证        4   20000.0   5785.68   \n",
      "134       ...       成功认证   成功认证  未成功认证  未成功认证        4  145000.0      0.00   \n",
      "164       ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10541.0   4663.32   \n",
      "166       ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10385.0   3205.13   \n",
      "169       ...      未成功认证   成功认证  未成功认证  未成功认证        3   12277.0   3930.21   \n",
      "170       ...       成功认证  未成功认证  未成功认证  未成功认证        4   12585.0   5163.72   \n",
      "172       ...       成功认证  未成功认证  未成功认证  未成功认证        5   17500.0   6233.32   \n",
      "186       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   1043.36   \n",
      "187       ...       成功认证  未成功认证  未成功认证  未成功认证        2   13290.0   3573.17   \n",
      "204       ...      未成功认证  未成功认证  未成功认证  未成功认证        2    7000.0   4141.49   \n",
      "205       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "208       ...      未成功认证  未成功认证  未成功认证  未成功认证        5   16120.0   8904.56   \n",
      "218       ...       成功认证  未成功认证  未成功认证  未成功认证        8   27529.0   5666.23   \n",
      "...       ...        ...    ...    ...    ...      ...       ...       ...   \n",
      "328435    ...      未成功认证   成功认证  未成功认证  未成功认证       10   19670.0   6127.41   \n",
      "328437    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    7000.0   1420.82   \n",
      "328448    ...      未成功认证  未成功认证  未成功认证  未成功认证        6   23269.0  11777.57   \n",
      "328453    ...      未成功认证   成功认证  未成功认证  未成功认证        6   17029.0   6990.83   \n",
      "328454    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1800.0   1369.96   \n",
      "328459    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6000.0   4106.89   \n",
      "328464    ...      未成功认证   成功认证  未成功认证  未成功认证        2    8744.0   3865.30   \n",
      "328465    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    3700.0   2975.74   \n",
      "328466    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    5500.0   3798.18   \n",
      "328468    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    4500.0   3107.58   \n",
      "328485    ...      未成功认证   成功认证  未成功认证  未成功认证        6    6953.0   5282.08   \n",
      "328486    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   10500.0   7973.21   \n",
      "328491    ...      未成功认证   成功认证  未成功认证  未成功认证        9   34520.0  18642.04   \n",
      "328494    ...      未成功认证   成功认证  未成功认证  未成功认证       10   14882.0   6704.93   \n",
      "328497    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2000.0   1359.71   \n",
      "328499    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   13500.0   7360.06   \n",
      "328501    ...      未成功认证   成功认证  未成功认证  未成功认证        5   16812.0   9743.68   \n",
      "328502    ...      未成功认证   成功认证  未成功认证  未成功认证        4   18836.0  10595.93   \n",
      "328507    ...      未成功认证   成功认证  未成功认证  未成功认证        1    4200.0   1502.89   \n",
      "328515    ...      未成功认证  未成功认证  未成功认证  未成功认证        4    2250.0    749.35   \n",
      "328520    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    4699.0   1148.68   \n",
      "328522    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    4500.0   3107.58   \n",
      "328525    ...       成功认证  未成功认证  未成功认证  未成功认证        5   20256.0  11434.94   \n",
      "328528    ...      未成功认证  未成功认证  未成功认证  未成功认证       10   32000.0  23591.95   \n",
      "328529    ...      未成功认证   成功认证   成功认证  未成功认证       11   39730.0  18516.42   \n",
      "328531    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    5426.0   2969.05   \n",
      "328532    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    5140.0   3692.90   \n",
      "328533    ...      未成功认证   成功认证  未成功认证  未成功认证        3   12475.0   7223.48   \n",
      "328535    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   14691.0  10087.86   \n",
      "328550    ...       成功认证  未成功认证  未成功认证  未成功认证        5   19656.0  10982.53   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "6             75         8   9.638554  \n",
      "8             41         2   4.651163  \n",
      "18             4         2  33.333333  \n",
      "22             8         0   0.000000  \n",
      "29            13         1   7.142857  \n",
      "41            10         0   0.000000  \n",
      "43             6         0   0.000000  \n",
      "45            10         2  16.666667  \n",
      "48            13         0   0.000000  \n",
      "49            10         0   0.000000  \n",
      "55            10         0   0.000000  \n",
      "78             3         0   0.000000  \n",
      "80             9         1  10.000000  \n",
      "81             7         0   0.000000  \n",
      "105            2         3  60.000000  \n",
      "106            7         1  12.500000  \n",
      "108           14         1   6.666667  \n",
      "110           29         0   0.000000  \n",
      "134           22         0   0.000000  \n",
      "164           12         0   0.000000  \n",
      "166            9         0   0.000000  \n",
      "169           14         0   0.000000  \n",
      "170           21         0   0.000000  \n",
      "172           18         1   5.263158  \n",
      "186            8         0   0.000000  \n",
      "187            5         0   0.000000  \n",
      "204            7         0   0.000000  \n",
      "205            3         0   0.000000  \n",
      "208           21         1   4.545455  \n",
      "218           45         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "328435        55         0   0.000000  \n",
      "328437        20         1   4.761905  \n",
      "328448        11        14  56.000000  \n",
      "328453        42         0   0.000000  \n",
      "328454         3         0   0.000000  \n",
      "328459         8         0   0.000000  \n",
      "328464         9         0   0.000000  \n",
      "328465         7         0   0.000000  \n",
      "328466         4         0   0.000000  \n",
      "328468         4         0   0.000000  \n",
      "328485        17         0   0.000000  \n",
      "328486         6         0   0.000000  \n",
      "328491        26         0   0.000000  \n",
      "328494        52         0   0.000000  \n",
      "328497         4         0   0.000000  \n",
      "328499        11         0   0.000000  \n",
      "328501        20         0   0.000000  \n",
      "328502        24         0   0.000000  \n",
      "328507         6         2  25.000000  \n",
      "328515        24         2   7.692308  \n",
      "328520        10         3  23.076923  \n",
      "328522         4         0   0.000000  \n",
      "328525        22         0   0.000000  \n",
      "328528        17         0   0.000000  \n",
      "328529        66         0   0.000000  \n",
      "328531         5         0   0.000000  \n",
      "328532         8         0   0.000000  \n",
      "328533         8         1  11.111111  \n",
      "328535         7         0   0.000000  \n",
      "328550        20         2   9.090909  \n",
      "\n",
      "[75191 rows x 22 columns])\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "male = LC[LC['性别']=='男']\n",
    "female = LC[LC['性别']=='女']\n",
    "sex=(male,female)\n",
    "sex_data=(male['借款金额'].sum(),female['借款金额'].sum())\n",
    "sex_idx=('男','女')\n",
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "plt.pie(sex_data,labels=sex_idx,autopct='%.1f%%')\n",
    "print(sex)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 新老客户分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:42.364795Z",
     "start_time": "2020-07-30T13:37:42.151917Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "new =LC[LC['是否首标']=='是']\n",
    "old = LC[LC['是否首标']=='否']\n",
    "newold_data = (new['借款金额'].sum(),old['借款金额'].sum())\n",
    "newold_idx =('新客户','老客户')\n",
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "plt.pie(newold_data,labels=newold_idx,autopct='%.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T12:04:33.112510Z",
     "start_time": "2020-07-30T12:04:33.094516Z"
    }
   },
   "source": [
    "### 学历分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:44.851387Z",
     "start_time": "2020-07-30T13:37:44.634494Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ungraduate = LC[LC['学历认证']=='未成功认证']\n",
    "graduate=LC[LC['学历认证']=='成功认证']\n",
    "education_data=(ungraduate['借款金额'].sum(),graduate['借款金额'].sum())\n",
    "education_idx=('大专以下','大专及以上')\n",
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "plt.pie(education_data,labels=education_idx,autopct='%.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T12:11:50.981987Z",
     "start_time": "2020-07-30T12:11:50.974971Z"
    }
   },
   "source": [
    "### 年龄分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:47.534310Z",
     "start_time": "2020-07-30T13:37:47.263489Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ageA=LC.loc[(LC['年龄']>=15) &  (LC['年龄']<20)]\n",
    "ageB=LC.loc[(LC['年龄']>=20) &  (LC['年龄']<25)]\n",
    "ageC=LC.loc[(LC['年龄']>=25) &  (LC['年龄']<30)]\n",
    "ageD=LC.loc[(LC['年龄']>=30) &  (LC['年龄']<35)]\n",
    "ageE=LC.loc[(LC['年龄']>=35) &  (LC['年龄']<40)]\n",
    "ageF=LC.loc[LC['年龄']>=40]\n",
    "age=[ageA,ageB,ageC,ageD,ageE,ageF]\n",
    "age_total=0\n",
    "age_percent=[]\n",
    "for i in age:\n",
    "    tmp=i['借款金额'].sum()\n",
    "    age_percent.append(tmp)\n",
    "    age_total+=tmp\n",
    "age_percent/=age_total\n",
    "age_idx = ['15-20', '20-25', '25-30', '30-35', '35-40', '40+']\n",
    "plt.figure(figsize=(15,8))\n",
    "plt.bar(age_idx,age_percent)\n",
    "for (a,b) in zip(age_idx,age_percent):\n",
    "    plt.text(a, b+0.001, '%.2f%%' % (b * 100), ha='center', va='bottom', fontsize=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T12:29:09.633949Z",
     "start_time": "2020-07-30T12:29:09.616978Z"
    }
   },
   "source": [
    "* 结论：\n",
    "\n",
    "    * 1.男性客户的贡献的贷款金额占到了69%，可能的原因是男性更倾向于提前消费且贷款金额较大。\n",
    "\n",
    "    * 2.非首标的金额占比达到66%，说明用户倾向于多次使用，产品粘性较高。\n",
    "\n",
    "    * 3.大专以下学历的贷款金额更多，但是由于可能有很多用户并未认证学历，所以数据存在出入。\n",
    "\n",
    "    * 4.年龄段在25-30岁之间的借款金额最多，而20-35岁的人群占比超过75%，是该产品的主力消费人群。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T12:25:40.990291Z",
     "start_time": "2020-07-30T12:25:40.976300Z"
    }
   },
   "source": [
    "# 每日的借款金额大概多少？波动有多大？公司每日需要准备多少资金可以保证不会出现资金短缺？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:49.807007Z",
     "start_time": "2020-07-30T13:37:49.795016Z"
    }
   },
   "outputs": [],
   "source": [
    "from datetime import   datetime\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析每日贷款金额走势"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:52.395542Z",
     "start_time": "2020-07-30T13:37:51.987757Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'每天贷款金额波动图')"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "loan=LC[['借款成功日期','借款金额']].copy()\n",
    "loan.loc[:,'借款日期']=pd.to_datetime(loan['借款成功日期'])\n",
    "loan1=loan.pivot_table(index='借款日期',aggfunc='sum').copy()\n",
    "plt.figure(figsize=(15, 6))\n",
    "plt.plot(loan1)\n",
    "plt.xlabel('日期')\n",
    "plt.ylabel('借款金额')\n",
    "plt.title('每天贷款金额波动图')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析每月贷款金额走势"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:57.188793Z",
     "start_time": "2020-07-30T13:37:54.537295Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "loan.loc[:,'借款成功月份'] = [datetime.strftime(x,'%Y-%m')  for x in loan['借款日期']]\n",
    "loan2 = loan.pivot_table(index='借款成功月份',aggfunc='sum').copy()\n",
    "plt.figure(figsize=(15, 6))\n",
    "plt.plot(loan2)\n",
    "plt.xlabel('月份')\n",
    "plt.xticks(['2015-01','2015-07','2016-01','2016-07','2017-01'])\n",
    "plt.ylabel('借款金额')\n",
    "plt.title('每月贷款金额波动图')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 对2017年1月的数据继续进行分析，并求出平均值和标准差"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:37:59.356588Z",
     "start_time": "2020-07-30T13:37:59.329545Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3950100.6333333333 1658485.8457435472\n"
     ]
    }
   ],
   "source": [
    "loan3=loan1.loc['2017-01']\n",
    "avg = loan3['借款金额'].mean()\n",
    "\n",
    "std =loan3['借款金额'].std()\n",
    "print(avg,std)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 结论：\n",
    "\n",
    "    * 1.每日贷款金额呈现的是一个往上的趋势,但是每天的波动较大。\n",
    "\n",
    "    * 2.每月贷款分析结论：从2015年1月到2017年1月，月度贷款金额呈现上升趋势，上升速度随着时间增快。\n",
    "\n",
    "    * 3.2017年1月每日的借款金额达到5204664元，标准差为2203394，根据3σ原则，想使每日借款金额充足的概率达到99.9%，则每日公式账上需准备5204664+2203394×3=11814846元。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 分析逾期还款率（借款人的初始评级、借款类型、性别、年龄、借款金额等特征）\n",
    "\n",
    "* 逾期还款率 = 历史逾期还款期数/（历史逾期还款期数+历史正常还款期数）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:00:32.485418Z",
     "start_time": "2020-07-30T13:00:32.467406Z"
    }
   },
   "source": [
    "### 初始评级的数据划分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:38:02.246918Z",
     "start_time": "2020-07-30T13:38:01.795133Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[        ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "5          162641  20000    12  14.0  2015-03-25    A     普通    否  36  男   \n",
      "110       1592201   5000     6  14.0  2015-01-04    A     普通    否  32  女   \n",
      "154       1612081   5000     3  14.0  2015-01-06    A     普通    否  38  男   \n",
      "157       1613631  10300     6  16.0  2015-01-14    A     普通    否  33  男   \n",
      "202       1633181   3600    12  14.0  2015-01-08    A     普通    否  28  男   \n",
      "209       1636111  28000    12  20.0  2015-01-08    A     其他    否  35  男   \n",
      "223       1643271   9000     3  18.0  2015-01-10    A     普通    否  37  男   \n",
      "282       1669131  13000    12  15.0  2015-01-14    A     其他    否  32  男   \n",
      "319       1678701   5000     3  14.0  2015-01-19    A     普通    否  33  男   \n",
      "324       1679601   4600    12  20.5  2015-01-20    A     普通    否  26  男   \n",
      "363       1690211   5722     6  16.0  2015-01-18    A     普通    否  29  男   \n",
      "364       1690831  12125    12  16.0  2015-01-21    A     其他    否  38  女   \n",
      "411       1705521   4300     6  14.0  2015-01-20    A     普通    否  33  女   \n",
      "425       1709031  10000    12  14.0  2015-01-22    A     普通    否  39  女   \n",
      "426       1709511  22000    12  14.0  2015-01-21    A     其他    否  39  男   \n",
      "471       1721271   4392    10  16.0  2015-01-27    A     普通    否  26  女   \n",
      "567       1748431   8861     6  18.0  2015-02-02    A     普通    否  35  男   \n",
      "571       1749021   8000     3  14.0  2015-02-02    A     普通    否  30  女   \n",
      "581       1751601   3800     6  17.0  2015-02-02    A     普通    否  32  男   \n",
      "585       1752151   6000     6  14.0  2015-02-03    A     普通    否  32  男   \n",
      "617       1762741   9296    12  16.0  2015-02-02    A     其他    否  40  男   \n",
      "683       1785651   5200    11  18.0  2015-02-05    A     普通    否  36  男   \n",
      "692       1789931  12000     6  14.0  2015-02-06    A     普通    否  29  女   \n",
      "707       1796821   5958     3  14.0  2015-02-06    A     普通    否  32  女   \n",
      "806       1837751   6888     6  16.0  2015-02-14    A     普通    否  38  男   \n",
      "829       1842511   4700    12  15.0  2015-02-15    A     普通    否  38  女   \n",
      "842       1848451   8800    12  18.0  2015-02-13    A     普通    否  29  男   \n",
      "853       1851431   3230     6  14.0  2015-02-15    A     普通    否  26  男   \n",
      "857       1851961   4382    12  18.0  2015-02-15    A     普通    否  28  女   \n",
      "906       1868971   5500    12  14.0  2015-02-25    A     普通    否  27  女   \n",
      "...           ...    ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "327261   32731361   5500    12  16.0  2017-01-29    A  APP闪电    否  26  男   \n",
      "327314   32738601  11100    12  16.0  2017-01-29    A     其他    否  28  女   \n",
      "327319   32739041   2000     6  20.0  2017-01-29    A     其他    否  23  女   \n",
      "327345   32740481   2177    12  16.0  2017-01-29    A     其他    否  28  女   \n",
      "327498   32748811   7000    12  16.0  2017-01-29    A     其他    否  27  女   \n",
      "327568   32753191   2315     6  20.0  2017-01-29    A     其他    否  23  女   \n",
      "327617   32757291   2376     3  16.0  2017-01-29    A     其他    否  25  男   \n",
      "327697   32760361  10333     6  16.0  2017-01-29    A     其他    否  27  女   \n",
      "327783   32765461   4967    12  18.0  2017-01-29    A     其他    否  22  男   \n",
      "327832   32769511   2969     9  18.0  2017-01-29    A     普通    否  28  女   \n",
      "327842   32770201   2000     6  16.0  2017-01-29    A     普通    否  27  女   \n",
      "327879   32773141   4000     8  16.0  2017-01-30    A     其他    否  32  男   \n",
      "327906   32775471   5042    12  16.0  2017-01-30    A  APP闪电    否  26  男   \n",
      "327927   32777111   1500     6  16.0  2017-01-30    A  APP闪电    否  28  女   \n",
      "327952   32780361   7308    12  18.0  2017-01-30    A     其他    否  26  男   \n",
      "327990   32783551   2000     6  20.0  2017-01-30    A     其他    否  25  男   \n",
      "328077   32788051   4000    12  16.0  2017-01-30    A     普通    否  23  女   \n",
      "328123   32790691   2034     3  16.0  2017-01-30    A     其他    否  25  女   \n",
      "328145   32791731   4260     9  16.0  2017-01-30    A     其他    否  24  男   \n",
      "328176   32793341   7308    11  16.0  2017-01-30    A     其他    否  26  男   \n",
      "328221   32796711   4357     6  16.0  2017-01-30    A  APP闪电    否  24  女   \n",
      "328238   32798561   3377    12  16.0  2017-01-30    A     其他    否  25  女   \n",
      "328240   32798731   1374     6  16.0  2017-01-30    A  APP闪电    否  33  女   \n",
      "328255   32799811   5900     6  16.0  2017-01-30    A  APP闪电    否  38  女   \n",
      "328281   32801691   2237    12  16.0  2017-01-30    A     其他    否  28  女   \n",
      "328292   32802361   6083     6  20.0  2017-01-30    A     其他    否  33  男   \n",
      "328307   32803171   5000    12  20.0  2017-01-30    A     其他    否  25  男   \n",
      "328344   32805071   5806    12  20.0  2017-01-30    A     普通    否  28  女   \n",
      "328432   32809531   7133     3  16.0  2017-01-30    A     普通    否  38  女   \n",
      "328491   32814011   2320     6  16.0  2017-01-30    A     其他    否  31  女   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  \\\n",
      "5         ...       成功认证  未成功认证  未成功认证  未成功认证        7   35622.0      0.00   \n",
      "110       ...       成功认证   成功认证  未成功认证  未成功认证        4   20000.0   5785.68   \n",
      "154       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "157       ...       成功认证   成功认证  未成功认证  未成功认证        5   33681.0   2713.47   \n",
      "202       ...       成功认证   成功认证  未成功认证  未成功认证        6   21638.0   8269.40   \n",
      "209       ...       成功认证   成功认证  未成功认证  未成功认证        5   40100.0   9534.38   \n",
      "223       ...       成功认证  未成功认证  未成功认证  未成功认证        9   73312.0   5835.82   \n",
      "282       ...      未成功认证   成功认证  未成功认证  未成功认证        3   11532.0   4064.64   \n",
      "319       ...       成功认证  未成功认证  未成功认证  未成功认证        7   33500.0   2553.29   \n",
      "324       ...      未成功认证   成功认证  未成功认证  未成功认证        4   16700.0   3856.29   \n",
      "363       ...      未成功认证   成功认证  未成功认证  未成功认证        2    7394.0      0.00   \n",
      "364       ...       成功认证   成功认证  未成功认证  未成功认证        4   17600.0   4604.10   \n",
      "411       ...      未成功认证   成功认证  未成功认证  未成功认证       14   52800.0  11836.68   \n",
      "425       ...      未成功认证  未成功认证  未成功认证  未成功认证        7   35250.0   5458.83   \n",
      "426       ...       成功认证   成功认证  未成功认证  未成功认证        7   50783.0   6171.39   \n",
      "471       ...       成功认证  未成功认证  未成功认证  未成功认证       11   62082.0  10737.46   \n",
      "567       ...       成功认证  未成功认证  未成功认证  未成功认证        4   20963.0   1637.49   \n",
      "571       ...      未成功认证   成功认证  未成功认证  未成功认证        2    9000.0      0.00   \n",
      "581       ...       成功认证  未成功认证  未成功认证  未成功认证        9   50569.0   9723.26   \n",
      "585       ...       成功认证   成功认证  未成功认证  未成功认证       12   65064.0   9871.45   \n",
      "617       ...      未成功认证  未成功认证  未成功认证  未成功认证        5   18281.0   6058.60   \n",
      "683       ...       成功认证  未成功认证  未成功认证  未成功认证       41  239598.0  24797.31   \n",
      "692       ...       成功认证  未成功认证  未成功认证  未成功认证       12   78800.0   3950.91   \n",
      "707       ...      未成功认证  未成功认证  未成功认证  未成功认证       17   73836.0   8042.45   \n",
      "806       ...       成功认证   成功认证  未成功认证  未成功认证       12   81976.0   4844.36   \n",
      "829       ...       成功认证  未成功认证  未成功认证  未成功认证        7   37400.0  10912.03   \n",
      "842       ...       成功认证  未成功认证  未成功认证  未成功认证       24  156132.0   7051.73   \n",
      "853       ...      未成功认证   成功认证  未成功认证  未成功认证        2    6000.0      0.00   \n",
      "857       ...      未成功认证   成功认证  未成功认证  未成功认证       10   42916.0   7748.98   \n",
      "906       ...       成功认证  未成功认证  未成功认证  未成功认证        9   45187.0  10058.86   \n",
      "...       ...        ...    ...    ...    ...      ...       ...       ...   \n",
      "327261    ...      未成功认证   成功认证  未成功认证  未成功认证        1    5000.0   4220.86   \n",
      "327314    ...      未成功认证   成功认证  未成功认证  未成功认证        1    8200.0      0.00   \n",
      "327319    ...       成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   2044.34   \n",
      "327345    ...      未成功认证   成功认证  未成功认证  未成功认证        5   25379.0  12314.58   \n",
      "327498    ...       成功认证   成功认证  未成功认证  未成功认证        3   15211.0   8667.59   \n",
      "327568    ...      未成功认证   成功认证  未成功认证  未成功认证        2   11260.0   7184.77   \n",
      "327617    ...      未成功认证   成功认证  未成功认证  未成功认证        6   32753.0  10223.60   \n",
      "327697    ...      未成功认证   成功认证  未成功认证  未成功认证        4   28238.0   9666.56   \n",
      "327783    ...      未成功认证   成功认证  未成功认证  未成功认证        2    5500.0   2032.88   \n",
      "327832    ...      未成功认证   成功认证  未成功认证  未成功认证        3   13212.0   7531.29   \n",
      "327842    ...      未成功认证   成功认证  未成功认证  未成功认证        2    9000.0   7390.35   \n",
      "327879    ...      未成功认证   成功认证  未成功认证  未成功认证        5   35700.0  15143.25   \n",
      "327906    ...      未成功认证   成功认证  未成功认证  未成功认证        1    6000.0   3657.86   \n",
      "327927    ...      未成功认证   成功认证  未成功认证  未成功认证        5   13400.0   5414.83   \n",
      "327952    ...      未成功认证   成功认证  未成功认证  未成功认证        2    9000.0   4191.48   \n",
      "327990    ...      未成功认证   成功认证  未成功认证  未成功认证        1    8200.0   4705.69   \n",
      "328077    ...      未成功认证   成功认证  未成功认证  未成功认证        3   12000.0   7575.69   \n",
      "328123    ...      未成功认证   成功认证  未成功认证  未成功认证        8   27515.0  10465.81   \n",
      "328145    ...      未成功认证   成功认证  未成功认证  未成功认证        4   23800.0  11739.37   \n",
      "328176    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   13500.0   4101.06   \n",
      "328221    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   10975.0   9665.97   \n",
      "328238    ...      未成功认证   成功认证  未成功认证  未成功认证        1    8600.0   6622.44   \n",
      "328240    ...      未成功认证  未成功认证  未成功认证  未成功认证        9   21451.0  13525.34   \n",
      "328255    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    5600.0      0.00   \n",
      "328281    ...       成功认证  未成功认证  未成功认证  未成功认证       17  103048.0  19762.52   \n",
      "328292    ...      未成功认证   成功认证  未成功认证  未成功认证        2   10586.0   5416.34   \n",
      "328307    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1500.0    896.68   \n",
      "328344    ...      未成功认证   成功认证  未成功认证  未成功认证        2    8006.0   1393.78   \n",
      "328432    ...      未成功认证   成功认证  未成功认证  未成功认证        1    5500.0   1866.87   \n",
      "328491    ...      未成功认证   成功认证  未成功认证  未成功认证        9   34520.0  18642.04   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "5             56         0   0.000000  \n",
      "110           29         0   0.000000  \n",
      "154            1         0   0.000000  \n",
      "157           21         1   4.545455  \n",
      "202           37         2   5.128205  \n",
      "209           23         0   0.000000  \n",
      "223           37         7  15.909091  \n",
      "282           11         1   8.333333  \n",
      "319           34         7  17.073171  \n",
      "324           22         2   8.333333  \n",
      "363            5         0   0.000000  \n",
      "364           13         2  13.333333  \n",
      "411           71         0   0.000000  \n",
      "425           49         2   3.921569  \n",
      "426           37         0   0.000000  \n",
      "471           87         1   1.136364  \n",
      "567           24         0   0.000000  \n",
      "571           11         1   8.333333  \n",
      "581           31         1   3.125000  \n",
      "585           89         1   1.111111  \n",
      "617           22         0   0.000000  \n",
      "683          268         0   0.000000  \n",
      "692           92         2   2.127660  \n",
      "707           50         0   0.000000  \n",
      "806           50         1   1.960784  \n",
      "829           45         7  13.461538  \n",
      "842          143         0   0.000000  \n",
      "853            2         2  50.000000  \n",
      "857           47        11  18.965517  \n",
      "906           52         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "327261         2         0   0.000000  \n",
      "327314         9         0   0.000000  \n",
      "327319         3         0   0.000000  \n",
      "327345        25         0   0.000000  \n",
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      "327842         3         0   0.000000  \n",
      "327879        16         0   0.000000  \n",
      "327906         5         0   0.000000  \n",
      "327927        19         0   0.000000  \n",
      "327952         7         1  12.500000  \n",
      "327990         4         0   0.000000  \n",
      "328077         8         0   0.000000  \n",
      "328123        47         1   2.083333  \n",
      "328145        24         0   0.000000  \n",
      "328176         6         0   0.000000  \n",
      "328221         7         0   0.000000  \n",
      "328238         3         0   0.000000  \n",
      "328240        68         0   0.000000  \n",
      "328255         6         0   0.000000  \n",
      "328281       133         0   0.000000  \n",
      "328292        12         0   0.000000  \n",
      "328307         5         0   0.000000  \n",
      "328344         4        12  75.000000  \n",
      "328432         4         0   0.000000  \n",
      "328491        26         0   0.000000  \n",
      "\n",
      "[8248 rows x 22 columns],         ListingId    借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "7          175451   20000    12  18.0  2016-03-19    B     普通    否  32  男   \n",
      "8          182261   25000    12  16.0  2015-03-21    B     其他    否  33  女   \n",
      "39        1551331    4691    12  18.0  2015-01-04    B     普通    否  45  男   \n",
      "43        1553501  400000     6  14.0  2015-01-03    B     电商    否  44  女   \n",
      "76        1578401  460000     6  14.0  2015-01-04    B     电商    否  38  男   \n",
      "80        1579171   10000    12  18.0  2015-01-07    B     普通    否  40  女   \n",
      "95        1585151    4525    12  22.0  2015-01-05    B     普通    否  30  男   \n",
      "140       1606911   54000     6  15.0  2015-01-05    B     电商    否  28  男   \n",
      "146       1607961    5000    10  16.0  2015-01-05    B     普通    否  37  男   \n",
      "169       1621581    3070     6  20.0  2015-01-06    B     普通    否  26  女   \n",
      "218       1642141   18000    12  16.0  2015-01-09    B     其他    否  31  女   \n",
      "228       1644011   40000     6  16.0  2015-01-12    B     电商    否  31  男   \n",
      "246       1652401    5000    12  20.0  2015-01-13    B     普通    否  25  男   \n",
      "257       1661461  229000     6  16.0  2015-01-13    B     电商    否  36  男   \n",
      "281       1668981    4800     6  16.0  2015-01-21    B     普通    否  35  男   \n",
      "313       1677551   50000     6  15.0  2015-01-18    B     电商    否  33  男   \n",
      "394       1700651    3345    10  16.0  2015-01-20    B     普通    否  30  男   \n",
      "465       1720151    4400     6  16.0  2015-01-22    B     普通    否  36  女   \n",
      "466       1720231    8000     6  16.0  2015-01-25    B     普通    否  33  男   \n",
      "470       1721161  156000     6  16.0  2015-01-30    B     电商    否  28  男   \n",
      "480       1723081    5419    12  16.0  2015-01-23    B     普通    否  36  男   \n",
      "531       1739641    4227     6  16.0  2015-01-30    B     普通    否  27  女   \n",
      "564       1748291    5000     6  18.0  2015-02-02    B     普通    否  32  男   \n",
      "570       1748971    5300     6  18.0  2015-02-03    B     普通    否  29  男   \n",
      "578       1751301    5300     6  16.0  2015-02-02    B     普通    否  31  男   \n",
      "580       1751561  200000     6  16.0  2015-02-06    B     电商    否  39  男   \n",
      "582       1751631  165000     6  14.0  2015-02-10    B     电商    否  32  男   \n",
      "583       1751741    3839    12  16.0  2015-02-05    B     普通    否  33  女   \n",
      "618       1762861    5042     6  16.0  2015-02-02    B     普通    否  26  女   \n",
      "623       1764351    4000    12  16.0  2015-02-11    B     普通    否  46  女   \n",
      "...           ...     ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328066   32787571    5300     9  18.0  2017-01-30    B     其他    否  28  男   \n",
      "328114   32790131    1071     6  18.0  2017-01-30    B  APP闪电    否  24  男   \n",
      "328141   32791291    6800    12  18.0  2017-01-30    B  APP闪电    否  26  男   \n",
      "328162   32792681    3000    12  18.0  2017-01-30    B     其他    否  25  女   \n",
      "328164   32792811    1098    12  18.0  2017-01-30    B  APP闪电    否  33  男   \n",
      "328180   32793721     649     6  18.0  2017-01-30    B  APP闪电    否  24  男   \n",
      "328192   32794731    1000    12  18.0  2017-01-30    B  APP闪电    否  24  男   \n",
      "328224   32797351    1300    12  18.0  2017-01-30    B  APP闪电    否  28  女   \n",
      "328270   32800691     720     6  18.0  2017-01-30    B  APP闪电    否  27  男   \n",
      "328294   32802401    6152     6  18.0  2017-01-30    B     其他    否  42  男   \n",
      "328301   32802611    2285     6  18.0  2017-01-30    B  APP闪电    否  25  女   \n",
      "328310   32803461    2970     6  18.0  2017-01-30    B     其他    否  25  女   \n",
      "328322   32804211     897     6  18.0  2017-01-30    B  APP闪电    否  35  女   \n",
      "328325   32804311    2500    12  18.0  2017-01-30    B  APP闪电    否  22  女   \n",
      "328327   32804361    1164    12  18.0  2017-01-30    B  APP闪电    否  30  男   \n",
      "328373   32806161    1783     6  18.0  2017-01-30    B  APP闪电    否  33  女   \n",
      "328405   32807751    7628    12  18.0  2017-01-30    B     其他    否  24  男   \n",
      "328422   32808661    2800     6  20.0  2017-01-30    B     其他    否  26  女   \n",
      "328431   32809301     776     6  18.0  2017-01-30    B  APP闪电    否  24  女   \n",
      "328435   32809711    3572     6  18.0  2017-01-30    B  APP闪电    否  26  女   \n",
      "328438   32809811    4134     6  20.0  2017-01-30    B     其他    否  28  男   \n",
      "328462   32811611    1996    12  18.0  2017-01-30    B  APP闪电    否  24  男   \n",
      "328465   32811921    1000    12  18.0  2017-01-30    B  APP闪电    否  19  女   \n",
      "328476   32812671    1868     6  18.0  2017-01-30    B  APP闪电    否  32  男   \n",
      "328490   32813831    2885    12  18.0  2017-01-30    B  APP闪电    否  30  男   \n",
      "328494   32814141     995    12  18.0  2017-01-30    B  APP闪电    否  35  女   \n",
      "328501   32814781    1556     6  18.0  2017-01-30    B  APP闪电    否  29  女   \n",
      "328524   32817221    5100    12  20.0  2017-01-30    B     普通    否  24  男   \n",
      "328525   32817231    2365    12  18.0  2017-01-30    B     其他    否  28  女   \n",
      "328529   32817621    5000    12  18.0  2017-01-30    B     其他    否  24  女   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额      总待还本金  \\\n",
      "7         ...       成功认证  未成功认证  未成功认证  未成功认证        7   35000.0    4078.61   \n",
      "8         ...       成功认证  未成功认证  未成功认证  未成功认证        7   42530.0    7418.35   \n",
      "39        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12788.0    7685.42   \n",
      "43        ...       成功认证  未成功认证  未成功认证  未成功认证        1  350000.0       0.00   \n",
      "76        ...      未成功认证  未成功认证  未成功认证  未成功认证        1  400000.0       0.00   \n",
      "80        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10328.0    3108.53   \n",
      "95        ...       成功认证   成功认证  未成功认证  未成功认证        5   25180.0    5198.01   \n",
      "140       ...       成功认证   成功认证  未成功认证  未成功认证        1   90000.0   45893.93   \n",
      "146       ...       成功认证  未成功认证  未成功认证  未成功认证        6   29600.0    6449.70   \n",
      "169       ...      未成功认证   成功认证  未成功认证  未成功认证        3   12277.0    3930.21   \n",
      "218       ...       成功认证  未成功认证  未成功认证  未成功认证        8   27529.0    5666.23   \n",
      "228       ...       成功认证  未成功认证  未成功认证  未成功认证        3  124500.0       0.00   \n",
      "246       ...      未成功认证  未成功认证  未成功认证  未成功认证        5   29200.0    8130.56   \n",
      "257       ...       成功认证  未成功认证  未成功认证  未成功认证        3  797000.0  100456.72   \n",
      "281       ...      未成功认证   成功认证  未成功认证  未成功认证        2    6900.0    4579.53   \n",
      "313       ...       成功认证   成功认证  未成功认证  未成功认证        1   40000.0       0.00   \n",
      "394       ...      未成功认证  未成功认证  未成功认证  未成功认证        4   12488.0    4861.46   \n",
      "465       ...       成功认证   成功认证  未成功认证  未成功认证        7   38199.0    8795.05   \n",
      "466       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0    1739.84   \n",
      "470       ...       成功认证  未成功认证  未成功认证  未成功认证        2  373000.0  113577.45   \n",
      "480       ...       成功认证  未成功认证  未成功认证  未成功认证        8   27232.0    4581.10   \n",
      "531       ...       成功认证  未成功认证  未成功认证  未成功认证        3    9000.0    2553.80   \n",
      "564       ...       成功认证  未成功认证  未成功认证  未成功认证        9   35956.0    3991.76   \n",
      "570       ...       成功认证  未成功认证  未成功认证  未成功认证        7   50900.0    7648.30   \n",
      "578       ...       成功认证   成功认证  未成功认证  未成功认证        6   31900.0   10693.00   \n",
      "580       ...       成功认证  未成功认证  未成功认证  未成功认证        2  550000.0       0.00   \n",
      "582       ...       成功认证  未成功认证  未成功认证  未成功认证        1  200000.0   34377.04   \n",
      "583       ...      未成功认证  未成功认证  未成功认证  未成功认证        5   26000.0    8093.47   \n",
      "618       ...      未成功认证   成功认证  未成功认证  未成功认证        4   14146.0       0.00   \n",
      "623       ...      未成功认证  未成功认证  未成功认证  未成功认证        5   21000.0    4766.18   \n",
      "...       ...        ...    ...    ...    ...      ...       ...        ...   \n",
      "328066    ...      未成功认证   成功认证  未成功认证  未成功认证        7   40620.0   20863.98   \n",
      "328114    ...      未成功认证  未成功认证  未成功认证  未成功认证       15   23875.0   11213.28   \n",
      "328141    ...      未成功认证   成功认证  未成功认证  未成功认证        4   14000.0    7233.52   \n",
      "328162    ...      未成功认证   成功认证  未成功认证  未成功认证        8   22679.0   13096.85   \n",
      "328164    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   15900.0   10201.59   \n",
      "328180    ...      未成功认证   成功认证  未成功认证  未成功认证        4    5091.0    1850.81   \n",
      "328192    ...      未成功认证   成功认证  未成功认证  未成功认证        2    1900.0    1437.42   \n",
      "328224    ...      未成功认证   成功认证  未成功认证  未成功认证        3    8547.0    5682.94   \n",
      "328270    ...      未成功认证   成功认证  未成功认证  未成功认证        4    6837.0    3779.66   \n",
      "328294    ...      未成功认证   成功认证  未成功认证  未成功认证        5   32716.0   15847.68   \n",
      "328301    ...      未成功认证   成功认证  未成功认证  未成功认证        7   12088.0    6314.25   \n",
      "328310    ...      未成功认证   成功认证  未成功认证  未成功认证        7   36188.0   18596.65   \n",
      "328322    ...      未成功认证  未成功认证  未成功认证  未成功认证        7   16688.0   11302.28   \n",
      "328325    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1500.0    1272.14   \n",
      "328327    ...      未成功认证   成功认证  未成功认证  未成功认证        5    9168.0    3735.66   \n",
      "328373    ...      未成功认证  未成功认证  未成功认证  未成功认证        5   11193.0    3716.53   \n",
      "328405    ...      未成功认证   成功认证  未成功认证  未成功认证        8   30134.0    9571.78   \n",
      "328422    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   11363.0    6699.78   \n",
      "328431    ...      未成功认证  未成功认证  未成功认证  未成功认证        5   12952.0    8723.10   \n",
      "328435    ...      未成功认证   成功认证  未成功认证  未成功认证       10   19670.0    6127.41   \n",
      "328438    ...      未成功认证   成功认证  未成功认证  未成功认证        3   15592.0    7085.83   \n",
      "328462    ...      未成功认证   成功认证  未成功认证  未成功认证        7   24433.0   15003.82   \n",
      "328465    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    3700.0    2975.74   \n",
      "328476    ...      未成功认证   成功认证  未成功认证  未成功认证        2   11000.0    6131.95   \n",
      "328490    ...      未成功认证   成功认证  未成功认证  未成功认证        6   15091.0    7514.90   \n",
      "328494    ...      未成功认证   成功认证  未成功认证  未成功认证       10   14882.0    6704.93   \n",
      "328501    ...      未成功认证   成功认证  未成功认证  未成功认证        5   16812.0    9743.68   \n",
      "328524    ...      未成功认证   成功认证  未成功认证  未成功认证        2    6164.0    4301.54   \n",
      "328525    ...       成功认证  未成功认证  未成功认证  未成功认证        5   20256.0   11434.94   \n",
      "328529    ...      未成功认证   成功认证   成功认证  未成功认证       11   39730.0   18516.42   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "7             52         0   0.000000  \n",
      "8             41         2   4.651163  \n",
      "39            17         0   0.000000  \n",
      "43             6         0   0.000000  \n",
      "76             4         2  33.333333  \n",
      "80             9         1  10.000000  \n",
      "95            24         4  14.285714  \n",
      "140            3         0   0.000000  \n",
      "146           29         0   0.000000  \n",
      "169           14         0   0.000000  \n",
      "218           45         0   0.000000  \n",
      "228           14         1   6.666667  \n",
      "246           36         0   0.000000  \n",
      "257           11         4  26.666667  \n",
      "281            4         1  20.000000  \n",
      "313            6         0   0.000000  \n",
      "394           26         0   0.000000  \n",
      "465           23         0   0.000000  \n",
      "466            2         1  33.333333  \n",
      "470            6         3  33.333333  \n",
      "480           38         0   0.000000  \n",
      "531           13         1   7.142857  \n",
      "564           47         0   0.000000  \n",
      "570           37         1   2.631579  \n",
      "578           21         0   0.000000  \n",
      "580            9         0   0.000000  \n",
      "582            5         0   0.000000  \n",
      "583           16         0   0.000000  \n",
      "618           11         0   0.000000  \n",
      "623           31         1   3.125000  \n",
      "...          ...       ...        ...  \n",
      "328066        29         0   0.000000  \n",
      "328114       118         0   0.000000  \n",
      "328141        23         0   0.000000  \n",
      "328162        35         0   0.000000  \n",
      "328164        17         0   0.000000  \n",
      "328180        20         0   0.000000  \n",
      "328192         5         0   0.000000  \n",
      "328224         9         0   0.000000  \n",
      "328270         9         0   0.000000  \n",
      "328294        18         0   0.000000  \n",
      "328301        20         0   0.000000  \n",
      "328310        27         0   0.000000  \n",
      "328322        21         2   8.695652  \n",
      "328325         2         0   0.000000  \n",
      "328327        15         0   0.000000  \n",
      "328373        15         0   0.000000  \n",
      "328405        65         2   2.985075  \n",
      "328422        10         0   0.000000  \n",
      "328431        14         0   0.000000  \n",
      "328435        55         0   0.000000  \n",
      "328438        21         0   0.000000  \n",
      "328462        47         0   0.000000  \n",
      "328465         7         0   0.000000  \n",
      "328476         9         0   0.000000  \n",
      "328490        31         0   0.000000  \n",
      "328494        52         0   0.000000  \n",
      "328501        20         0   0.000000  \n",
      "328524         5         3  37.500000  \n",
      "328525        22         0   0.000000  \n",
      "328529        66         0   0.000000  \n",
      "\n",
      "[24305 rows x 22 columns],         ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "0          126541  18000    12  18.0  2015-05-04    C     其他    否  35  男   \n",
      "3          149711  25000    12  18.0  2015-03-30    C     其他    否  34  男   \n",
      "4          152141  20000     6  16.0  2015-01-22    C     电商    否  24  男   \n",
      "9          193831  10475     6  18.0  2015-04-15    C     电商    否  25  男   \n",
      "14         528911  11000    12  20.0  2015-03-10    C     其他    否  47  男   \n",
      "15        1080421   5250     6  18.0  2015-05-27    C     电商    否  25  男   \n",
      "21        1537661   8000    12  20.0  2015-01-04    C     普通    否  39  男   \n",
      "27        1542581   3500    12  18.0  2015-01-04    C     普通    否  28  男   \n",
      "28        1542681  13083    12  18.0  2015-01-04    C     普通    否  46  男   \n",
      "29        1542821  11748    12  18.0  2015-01-04    C     普通    否  29  女   \n",
      "30        1546771  12000    12  18.0  2015-01-04    C     普通    否  27  男   \n",
      "33        1548521  10053    12  18.0  2015-01-07    C     普通    否  34  男   \n",
      "35        1549891   4940    12  22.0  2015-01-02    C     普通    否  24  男   \n",
      "38        1551311   8500    12  20.0  2015-01-04    C     普通    否  31  男   \n",
      "41        1551961   8972    12  18.0  2015-01-06    C     普通    否  31  女   \n",
      "42        1553151   8000    12  18.0  2015-01-07    C     普通    否  36  男   \n",
      "47        1557211  10660    12  20.0  2015-01-05    C     普通    否  27  男   \n",
      "48        1557241   9243    12  18.0  2015-01-07    C     其他    否  28  女   \n",
      "49        1558081  10000    12  18.0  2015-01-07    C     普通    否  30  女   \n",
      "50        1558481   5000    10  18.0  2015-01-07    C     普通    否  26  男   \n",
      "52        1559191  12383    12  20.0  2015-01-07    C     其他    否  32  男   \n",
      "53        1559261  10000    12  18.0  2015-01-07    C     其他    否  36  男   \n",
      "54        1559401  15000    12  20.0  2015-01-07    C     普通    否  46  男   \n",
      "55        1560101  10000    12  16.0  2015-01-07    C     普通    否  34  女   \n",
      "56        1560601   3879    12  18.0  2015-01-07    C     普通    否  48  男   \n",
      "58        1563891   3500    12  20.0  2015-01-02    C     普通    否  38  男   \n",
      "60        1568981  15000    12  20.0  2015-01-07    C     其他    否  33  男   \n",
      "65        1572791   8000    12  18.0  2015-01-07    C     普通    否  26  男   \n",
      "67        1572971  10000    12  18.0  2015-01-07    C     普通    否  30  男   \n",
      "73        1574701  10000    12  20.0  2015-01-07    C     其他    否  26  男   \n",
      "...           ...    ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328493   32814121   2500     6  20.0  2017-01-30    C     其他    否  36  男   \n",
      "328495   32814151   3900    12  20.0  2017-01-30    C     普通    否  22  男   \n",
      "328497   32814351   5000     6  20.0  2017-01-30    C     其他    否  39  女   \n",
      "328498   32814491   3000    12  20.0  2017-01-30    C     其他    否  25  男   \n",
      "328500   32814731   2696    12  20.0  2017-01-30    C     普通    否  41  男   \n",
      "328502   32814971   2354    12  16.0  2017-01-30    C     其他    否  23  女   \n",
      "328506   32815221   4782    12  20.0  2017-01-30    C     其他    否  23  男   \n",
      "328507   32815401   4497    12  22.0  2017-01-30    C     其他    否  38  女   \n",
      "328508   32815411   2000    10  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328517   32816441   2500    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328520   32817051   2351     6  20.0  2017-01-30    C     其他    否  53  女   \n",
      "328523   32817151   4564     6  20.0  2017-01-30    C     其他    否  30  男   \n",
      "328526   32817361   7354    12  20.0  2017-01-30    C     普通    否  25  男   \n",
      "328527   32817401   1200    12  20.0  2017-01-30    C  APP闪电    否  22  男   \n",
      "328528   32817451   2000     6  18.0  2017-01-30    C     其他    否  27  女   \n",
      "328530   32817701   1041    12  20.0  2017-01-30    C     普通    否  24  男   \n",
      "328533   32817951   2000    12  20.0  2017-01-30    C     普通    否  26  女   \n",
      "328534   32818011    728    12  20.0  2017-01-30    C  APP闪电    否  36  男   \n",
      "328535   32818041    782     6  20.0  2017-01-30    C  APP闪电    否  38  女   \n",
      "328537   32818161   2873     6  16.0  2017-01-30    C     普通    否  28  男   \n",
      "328539   32818231   2256     6  20.0  2017-01-30    C     其他    否  39  男   \n",
      "328540   32818411   1814    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328542   32818621   3500     6  20.0  2017-01-30    C     其他    否  34  男   \n",
      "328543   32818851   5804    12  20.0  2017-01-30    C     其他    否  44  男   \n",
      "328544   32818871   6880     6  20.0  2017-01-30    C     其他    否  28  男   \n",
      "328545   32818901   5008    12  20.0  2017-01-30    C     其他    否  28  男   \n",
      "328548   32819271   2389     6  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328549   32819381   7000    12  20.0  2017-01-30    C     其他    否  22  男   \n",
      "328550   32819451   2017     6  20.0  2017-01-30    C     其他    否  36  女   \n",
      "328551   32819511   6406    12  20.0  2017-01-30    C     其他    否  33  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  \\\n",
      "0         ...       成功认证  未成功认证  未成功认证  未成功认证       11   40326.0   8712.73   \n",
      "3         ...       成功认证  未成功认证  未成功认证  未成功认证        6   36190.0   9703.41   \n",
      "4         ...       成功认证  未成功认证  未成功认证  未成功认证       13   77945.0      0.00   \n",
      "9         ...       成功认证  未成功认证  未成功认证  未成功认证        9  107000.0      0.00   \n",
      "14        ...      未成功认证  未成功认证  未成功认证  未成功认证        5   17809.0   3589.14   \n",
      "15        ...       成功认证  未成功认证  未成功认证   成功认证        7  379000.0  10745.88   \n",
      "21        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "27        ...       成功认证  未成功认证  未成功认证  未成功认证        3    9399.0   3130.15   \n",
      "28        ...       成功认证   成功认证  未成功认证  未成功认证        5   22100.0   6015.72   \n",
      "29        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12000.0   6766.82   \n",
      "30        ...      未成功认证   成功认证  未成功认证  未成功认证        6   23000.0   7633.48   \n",
      "33        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10000.0   4393.83   \n",
      "35        ...       成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "38        ...       成功认证   成功认证  未成功认证  未成功认证        3   11900.0      0.00   \n",
      "41        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12200.0   4796.70   \n",
      "42        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0    786.71   \n",
      "47        ...       成功认证   成功认证  未成功认证  未成功认证        3   11800.0   5578.70   \n",
      "48        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10000.0   4430.56   \n",
      "49        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   21000.0   5041.21   \n",
      "50        ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6000.0    786.87   \n",
      "52        ...      未成功认证   成功认证  未成功认证  未成功认证        4   15232.0   4598.51   \n",
      "53        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   15051.0   5177.22   \n",
      "54        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   14447.0   4211.26   \n",
      "55        ...      未成功认证  未成功认证  未成功认证  未成功认证        3    9741.0   5642.67   \n",
      "56        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   15265.0   6845.33   \n",
      "58        ...       成功认证   成功认证  未成功认证  未成功认证        3    9400.0   4770.64   \n",
      "60        ...      未成功认证   成功认证  未成功认证  未成功认证        6   24357.0   3951.51   \n",
      "65        ...      未成功认证   成功认证  未成功认证  未成功认证        2    8000.0      0.00   \n",
      "67        ...       成功认证   成功认证  未成功认证  未成功认证        3   11237.0   5449.41   \n",
      "73        ...      未成功认证   成功认证  未成功认证  未成功认证        2    8000.0   5244.08   \n",
      "...       ...        ...    ...    ...    ...      ...       ...       ...   \n",
      "328493    ...       成功认证   成功认证  未成功认证  未成功认证        7   32240.0  21324.96   \n",
      "328495    ...      未成功认证   成功认证  未成功认证  未成功认证        4    8969.0   5599.62   \n",
      "328497    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2000.0   1359.71   \n",
      "328498    ...      未成功认证   成功认证  未成功认证  未成功认证        4   16500.0  11211.00   \n",
      "328500    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    8823.0   6303.85   \n",
      "328502    ...      未成功认证   成功认证  未成功认证  未成功认证        4   18836.0  10595.93   \n",
      "328506    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1600.0   1217.74   \n",
      "328507    ...      未成功认证   成功认证  未成功认证  未成功认证        1    4200.0   1502.89   \n",
      "328508    ...      未成功认证   成功认证  未成功认证  未成功认证        2    5000.0   4359.71   \n",
      "328517    ...      未成功认证   成功认证  未成功认证  未成功认证        3    2000.0   1438.58   \n",
      "328520    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    4699.0   1148.68   \n",
      "328523    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3200.0   2435.46   \n",
      "328526    ...      未成功认证   成功认证  未成功认证  未成功认证        6   30639.0  10175.77   \n",
      "328527    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1750.0    603.74   \n",
      "328528    ...      未成功认证  未成功认证  未成功认证  未成功认证       10   32000.0  23591.95   \n",
      "328530    ...       成功认证  未成功认证  未成功认证  未成功认证        4    4415.0   3058.81   \n",
      "328533    ...      未成功认证   成功认证  未成功认证  未成功认证        3   12475.0   7223.48   \n",
      "328534    ...      未成功认证   成功认证  未成功认证  未成功认证        7   10948.0   6271.30   \n",
      "328535    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   14691.0  10087.86   \n",
      "328537    ...       成功认证   成功认证   成功认证  未成功认证        9   33377.0  18207.50   \n",
      "328539    ...      未成功认证   成功认证  未成功认证  未成功认证        6   27142.0  15743.41   \n",
      "328540    ...      未成功认证   成功认证  未成功认证  未成功认证        2    5000.0   2885.30   \n",
      "328542    ...      未成功认证   成功认证  未成功认证  未成功认证        7   26502.0   6916.73   \n",
      "328543    ...      未成功认证   成功认证  未成功认证  未成功认证        3   12421.0   5395.26   \n",
      "328544    ...      未成功认证   成功认证  未成功认证  未成功认证        5   19208.0  16184.84   \n",
      "328545    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   10500.0   7727.37   \n",
      "328548    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   10000.0   7610.82   \n",
      "328549    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2100.0      0.00   \n",
      "328550    ...       成功认证  未成功认证  未成功认证  未成功认证        5   19656.0  10982.53   \n",
      "328551    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3500.0   1593.59   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "0             57        16  21.917808  \n",
      "3             41         1   2.380952  \n",
      "4            118        14  10.606061  \n",
      "9             49         4   7.547170  \n",
      "14            25         2   7.407407  \n",
      "15            31         2   6.060606  \n",
      "21             1         0   0.000000  \n",
      "27            10         0   0.000000  \n",
      "28            19         0   0.000000  \n",
      "29            13         1   7.142857  \n",
      "30            34         4  10.526316  \n",
      "33            12         0   0.000000  \n",
      "35             4         0   0.000000  \n",
      "38            12         0   0.000000  \n",
      "41            10         0   0.000000  \n",
      "42             9         0   0.000000  \n",
      "47            12         0   0.000000  \n",
      "48            13         0   0.000000  \n",
      "49            10         0   0.000000  \n",
      "50            13         3  18.750000  \n",
      "52            18         0   0.000000  \n",
      "53            14         0   0.000000  \n",
      "54            19         0   0.000000  \n",
      "55            10         0   0.000000  \n",
      "56            14         0   0.000000  \n",
      "58            10         0   0.000000  \n",
      "60            24         3  11.111111  \n",
      "65             8         0   0.000000  \n",
      "67            11         0   0.000000  \n",
      "73             9         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "328493         9         2  18.181818  \n",
      "328495        16         0   0.000000  \n",
      "328497         4         0   0.000000  \n",
      "328498        15         0   0.000000  \n",
      "328500        10         0   0.000000  \n",
      "328502        24         0   0.000000  \n",
      "328506         2         1  33.333333  \n",
      "328507         6         2  25.000000  \n",
      "328508         4         0   0.000000  \n",
      "328517         8         0   0.000000  \n",
      "328520        10         3  23.076923  \n",
      "328523         3         0   0.000000  \n",
      "328526        33         5  13.157895  \n",
      "328527         8         0   0.000000  \n",
      "328528        17         0   0.000000  \n",
      "328530        16         0   0.000000  \n",
      "328533         8         1  11.111111  \n",
      "328534        28         0   0.000000  \n",
      "328535         7         0   0.000000  \n",
      "328537        26         1   3.703704  \n",
      "328539        24         0   0.000000  \n",
      "328540         7         0   0.000000  \n",
      "328542        45         0   0.000000  \n",
      "328543        15         1   6.250000  \n",
      "328544         9         2  18.181818  \n",
      "328545        14         0   0.000000  \n",
      "328548         3         0   0.000000  \n",
      "328549        12         0   0.000000  \n",
      "328550        20         2   9.090909  \n",
      "328551         7         0   0.000000  \n",
      "\n",
      "[117976 rows x 22 columns],         ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "1          133291   9453    12  20.0  2015-03-16    D     其他    否  34  男   \n",
      "16        1518801   4913    12  24.0  2015-01-01    D     普通    否  26  男   \n",
      "22        1538211   3000    12  20.0  2015-01-04    D     普通    否  23  女   \n",
      "23        1540111  12778    12  20.0  2015-01-04    D     普通    否  26  男   \n",
      "24        1541631  10000    12  20.0  2015-01-04    D     普通    否  38  男   \n",
      "25        1541641  11578    12  20.0  2015-01-04    D     其他    否  27  男   \n",
      "26        1541761  10000    12  20.0  2015-01-04    D     普通    否  29  男   \n",
      "32        1548231   8000    12  20.0  2015-01-04    D     其他    否  27  男   \n",
      "36        1550751   3500    12  20.0  2015-01-05    D     普通    否  27  男   \n",
      "37        1551201   3884    12  22.0  2015-01-05    D     普通    否  25  男   \n",
      "40        1551871   3500    12  21.0  2015-01-05    D     普通    否  23  男   \n",
      "44        1554311   9000     6  18.0  2015-01-04    D     普通    否  25  男   \n",
      "45        1555121   3158    12  20.0  2015-01-07    D     普通    否  23  女   \n",
      "51        1558971   3714    12  20.0  2015-01-06    D     普通    否  27  男   \n",
      "59        1565761   3974    12  22.0  2015-01-03    D     普通    否  37  男   \n",
      "63        1570471   3000    12  20.0  2015-01-05    D     普通    否  24  男   \n",
      "64        1571061   4890    12  22.0  2015-01-04    D     普通    否  24  男   \n",
      "66        1572871   3000    12  22.0  2015-01-01    D     普通    否  28  男   \n",
      "68        1573151   5298    12  24.0  2015-01-01    D     普通    否  27  男   \n",
      "69        1573191   5000    12  20.0  2015-01-07    D     普通    否  23  男   \n",
      "70        1573441  12831    12  22.0  2015-01-07    D     其他    否  27  男   \n",
      "88        1581371   4000    12  20.0  2015-01-07    D     普通    否  28  男   \n",
      "89        1582411   1000     7  23.0  2015-01-06    D     普通    否  22  男   \n",
      "96        1585561  10000    12  20.0  2015-01-07    D     其他    否  45  男   \n",
      "100       1586561   3800    12  20.0  2015-01-08    D     普通    否  31  男   \n",
      "101       1586721   4450    12  24.0  2015-01-05    D     普通    否  27  男   \n",
      "102       1586811   1000     7  23.0  2015-01-04    D     普通    否  21  男   \n",
      "108       1590361   4284    12  20.0  2015-01-07    D     普通    否  31  女   \n",
      "111       1592951   4149    12  22.0  2015-01-05    D     普通    否  26  男   \n",
      "120       1595991   4500    12  20.0  2015-01-07    D     普通    否  34  男   \n",
      "...           ...    ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328468   32812091   2200    12  22.0  2017-01-30    D  APP闪电    否  26  女   \n",
      "328471   32812331   1179    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "328472   32812341   1000    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328474   32812631   1581    12  22.0  2017-01-30    D  APP闪电    否  29  男   \n",
      "328477   32812681   2482    12  22.0  2017-01-30    D     普通    否  28  男   \n",
      "328480   32813011   2000    12  22.0  2017-01-30    D     其他    否  25  男   \n",
      "328489   32813661   2800    12  22.0  2017-01-30    D  APP闪电    否  32  男   \n",
      "328492   32814071    955    12  22.0  2017-01-30    D  APP闪电    否  41  男   \n",
      "328496   32814211   1313    12  22.0  2017-01-30    D  APP闪电    否  27  男   \n",
      "328499   32814611   2119     6  20.0  2017-01-30    D     其他    否  40  女   \n",
      "328504   32815111   4201    12  22.0  2017-01-30    D  APP闪电    否  45  男   \n",
      "328505   32815181   5000    12  22.0  2017-01-30    D     普通    否  41  男   \n",
      "328509   32815421   1396    12  22.0  2017-01-30    D  APP闪电    否  35  男   \n",
      "328510   32815471   2571    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328511   32815751    990    12  22.0  2017-01-30    D  APP闪电    否  36  男   \n",
      "328512   32815861   4000    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328513   32815871   3327    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328515   32816321    700    12  22.0  2017-01-30    D  APP闪电    否  22  女   \n",
      "328516   32816401   3548    12  20.0  2017-01-30    D     普通    否  38  男   \n",
      "328518   32816561   2431    12  22.0  2017-01-30    D     其他    否  43  男   \n",
      "328519   32816991   2000     6  20.0  2017-01-30    D     其他    否  35  男   \n",
      "328522   32817131   3592    12  22.0  2017-01-30    D  APP闪电    否  31  女   \n",
      "328531   32817811    730    12  22.0  2017-01-30    D  APP闪电    否  30  女   \n",
      "328532   32817821   2807    12  22.0  2017-01-30    D     其他    否  38  女   \n",
      "328536   32818051   1175    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328538   32818171   1677    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328541   32818591   2067    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328546   32818911    782    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "328547   32818941   2200    12  22.0  2017-01-30    D     其他    否  32  男   \n",
      "328552   32819531   3440    12  22.0  2017-01-30    D     其他    否  27  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "1         ...      未成功认证  未成功认证  未成功认证  未成功认证        4  14500.0   7890.64   \n",
      "16        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "22        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1043.36   \n",
      "23        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  12700.0   1703.56   \n",
      "24        ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "25        ...       成功认证  未成功认证  未成功认证  未成功认证        4  20366.0   8378.53   \n",
      "26        ...      未成功认证   成功认证  未成功认证  未成功认证        3   9500.0   5452.42   \n",
      "32        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "36        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10500.0   6078.40   \n",
      "37        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "40        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  13500.0   8607.48   \n",
      "44        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "45        ...       成功认证  未成功认证  未成功认证  未成功认证        2   6300.0   1454.93   \n",
      "51        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0    880.34   \n",
      "59        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   2921.14   \n",
      "63        ...      未成功认证   成功认证  未成功认证  未成功认证        3  10500.0   4592.65   \n",
      "64        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  14747.0   6703.83   \n",
      "66        ...      未成功认证   成功认证  未成功认证  未成功认证        6  20600.0   6445.07   \n",
      "68        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "69        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0    896.34   \n",
      "70        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  13518.0   7250.91   \n",
      "88        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10196.0   5944.84   \n",
      "89        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "96        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7000.0   3349.81   \n",
      "100       ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10564.0   4157.18   \n",
      "101       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "102       ...       成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "108       ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9499.0   5747.85   \n",
      "111       ...      未成功认证   成功认证  未成功认证  未成功认证        2   6140.0   2994.38   \n",
      "120       ...       成功认证  未成功认证  未成功认证  未成功认证        2   6500.0   3252.03   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "328468    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3107.58   \n",
      "328471    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   7728.0   4320.62   \n",
      "328472    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1200.0      0.00   \n",
      "328474    ...      未成功认证  未成功认证  未成功认证  未成功认证        8  16526.0   8218.49   \n",
      "328477    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6136.0   4518.14   \n",
      "328480    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0    679.87   \n",
      "328489    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  10667.0   3993.59   \n",
      "328492    ...      未成功认证   成功认证  未成功认证  未成功认证        1   4000.0   3044.33   \n",
      "328496    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5500.0   3786.48   \n",
      "328499    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  13500.0   7360.06   \n",
      "328504    ...      未成功认证  未成功认证  未成功认证  未成功认证        2  10500.0   6098.62   \n",
      "328505    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5000.0    384.47   \n",
      "328509    ...      未成功认证  未成功认证  未成功认证  未成功认证       11  16254.0   6303.57   \n",
      "328510    ...      未成功认证  未成功认证  未成功认证  未成功认证       10  16548.0   6328.08   \n",
      "328511    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1500.0    509.15   \n",
      "328512    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4000.0      0.00   \n",
      "328513    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0    672.73   \n",
      "328515    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   2250.0    749.35   \n",
      "328516    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  22360.0  11877.89   \n",
      "328518    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  19842.0   8068.86   \n",
      "328519    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   8000.0   4982.88   \n",
      "328522    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3107.58   \n",
      "328531    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5426.0   2969.05   \n",
      "328532    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5140.0   3692.90   \n",
      "328536    ...       成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3424.88   \n",
      "328538    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   4805.0   2422.66   \n",
      "328541    ...      未成功认证   成功认证  未成功认证  未成功认证        2   3993.0   3332.43   \n",
      "328546    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4818.0   3217.74   \n",
      "328547    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7200.0   1154.51   \n",
      "328552    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3059.31   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "1             13         1   7.142857  \n",
      "16             2         0   0.000000  \n",
      "22             8         0   0.000000  \n",
      "23            19         0   0.000000  \n",
      "24             6         1  14.285714  \n",
      "25             9         0   0.000000  \n",
      "26             5         2  28.571429  \n",
      "32             7         0   0.000000  \n",
      "36            13         0   0.000000  \n",
      "37             2         0   0.000000  \n",
      "40            13         0   0.000000  \n",
      "44             6         1  14.285714  \n",
      "45            10         2  16.666667  \n",
      "51             5         0   0.000000  \n",
      "59            10         0   0.000000  \n",
      "63            13         0   0.000000  \n",
      "64            19         0   0.000000  \n",
      "66            24         2   7.692308  \n",
      "68             3         0   0.000000  \n",
      "69             5         0   0.000000  \n",
      "70            18         0   0.000000  \n",
      "88            16         0   0.000000  \n",
      "89             7         0   0.000000  \n",
      "96             8         0   0.000000  \n",
      "100            8         0   0.000000  \n",
      "101            4         0   0.000000  \n",
      "102            4         0   0.000000  \n",
      "108           14         1   6.666667  \n",
      "111            7         0   0.000000  \n",
      "120            7         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "328468         4         0   0.000000  \n",
      "328471         7         0   0.000000  \n",
      "328472         6         0   0.000000  \n",
      "328474        27         0   0.000000  \n",
      "328477         7         0   0.000000  \n",
      "328480         4         0   0.000000  \n",
      "328489        18         0   0.000000  \n",
      "328492         3         0   0.000000  \n",
      "328496         4         0   0.000000  \n",
      "328499        11         0   0.000000  \n",
      "328504         8         0   0.000000  \n",
      "328505        11         2  15.384615  \n",
      "328509        52         0   0.000000  \n",
      "328510        45         0   0.000000  \n",
      "328511         3         1  25.000000  \n",
      "328512         6         0   0.000000  \n",
      "328513         2         0   0.000000  \n",
      "328515        24         2   7.692308  \n",
      "328516        24         0   0.000000  \n",
      "328518        21        10  32.258065  \n",
      "328519        13         0   0.000000  \n",
      "328522         4         0   0.000000  \n",
      "328531         5         0   0.000000  \n",
      "328532         8         0   0.000000  \n",
      "328536         3         0   0.000000  \n",
      "328538        10         0   0.000000  \n",
      "328541         4         0   0.000000  \n",
      "328546         4         1  20.000000  \n",
      "328547        15         3  16.666667  \n",
      "328552         4         0   0.000000  \n",
      "\n",
      "[82038 rows x 22 columns],         ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别  \\\n",
      "2          142421  27000    24  20.0  2016-04-26    E   普通    否  41  男   \n",
      "6          171191   3940     6  18.0  2015-06-26    E   电商    否  27  女   \n",
      "10         199461  25000    12  20.0  2015-11-29    E   普通    否  29  男   \n",
      "11         209191  20000    12  20.0  2015-11-28    E   普通    否  33  男   \n",
      "12         209381  30000    24  16.0  2015-06-28    E   其他    否  30  男   \n",
      "13         223081  26000    12  20.0  2016-06-28    E   普通    否  35  男   \n",
      "31        1547751   3900    12  23.0  2015-01-04    E   普通    否  27  男   \n",
      "61        1569321   3700    12  22.0  2015-01-09    E   普通    否  28  男   \n",
      "62        1569871   4444    12  22.0  2015-01-02    E   普通    否  39  男   \n",
      "71        1573751   3200    12  22.0  2015-01-10    E   普通    否  34  男   \n",
      "72        1574051   3200    12  22.0  2015-01-08    E   普通    否  31  男   \n",
      "94        1584961   3700    12  22.0  2015-01-08    E   普通    否  32  男   \n",
      "103       1587191   6400    12  22.0  2015-01-08    E   普通    否  28  男   \n",
      "106       1589451   8109    12  22.0  2015-01-07    E   普通    否  31  女   \n",
      "116       1595141   3600    12  22.0  2015-01-09    E   普通    否  27  男   \n",
      "121       1596281   3000     6  18.0  2015-01-05    E   普通    否  34  男   \n",
      "128       1601641   4721    12  22.0  2015-01-06    E   普通    否  23  男   \n",
      "129       1602331   4500    12  22.0  2015-01-08    E   普通    否  25  男   \n",
      "131       1603021   3200    12  22.0  2015-01-12    E   普通    否  47  男   \n",
      "144       1607771  10000    12  20.0  2015-01-14    E   其他    否  29  男   \n",
      "172       1622451   3009    12  22.0  2015-01-07    E   普通    否  25  女   \n",
      "176       1623301   9734    12  20.0  2015-01-06    E   其他    否  23  男   \n",
      "180       1624971   6886    12  22.0  2015-01-21    E   普通    否  24  男   \n",
      "203       1633191   3200    12  22.0  2015-01-09    E   普通    否  27  男   \n",
      "216       1639111   1000     7  23.0  2015-01-09    E   普通    否  21  男   \n",
      "253       1658681   4154    12  22.0  2015-01-23    E   普通    否  30  男   \n",
      "255       1660461   3400    12  24.0  2015-01-16    E   普通    否  32  男   \n",
      "283       1669231   4889    12  22.0  2015-01-20    E   普通    否  23  男   \n",
      "293       1672021   4060    12  22.0  2015-01-27    E   普通    否  36  女   \n",
      "300       1673201   4353    12  24.0  2015-01-16    E   普通    否  27  男   \n",
      "...           ...    ...   ...   ...         ...  ...  ...  ...  .. ..   \n",
      "326625   32690241   2087    12  22.0  2017-01-28    E   普通    否  29  男   \n",
      "326700   32698421   2138    12  22.0  2017-01-28    E   其他    否  27  女   \n",
      "326756   32701241   2000    12  22.0  2017-01-28    E   其他    否  32  男   \n",
      "326790   32703061   4164    12  22.0  2017-01-29    E   其他    否  26  男   \n",
      "326828   32705451   2538    12  22.0  2017-01-29    E   其他    否  29  男   \n",
      "326838   32705741   5968    12  22.0  2017-01-28    E   普通    否  25  男   \n",
      "326869   32707971   4000    12  22.0  2017-01-29    E   其他    否  31  女   \n",
      "326883   32709511   2299    12  22.0  2017-01-28    E   其他    否  36  男   \n",
      "326949   32713711   2000    12  22.0  2017-01-29    E   普通    否  28  女   \n",
      "326975   32714311   3500    12  22.0  2017-01-29    E   其他    否  44  男   \n",
      "326986   32714521   3751    12  22.0  2017-01-29    E   普通    否  23  男   \n",
      "327000   32715121   3196    12  22.0  2017-01-29    E   普通    否  50  男   \n",
      "327004   32715191   3888    12  22.0  2017-01-29    E   其他    否  29  男   \n",
      "327063   32717571   6004    12  22.0  2017-01-29    E   普通    否  24  女   \n",
      "327106   32720051   2037    12  22.0  2017-01-29    E   普通    否  32  男   \n",
      "327144   32722551   4652    12  22.0  2017-01-29    E   普通    否  33  男   \n",
      "327195   32726091   2647    12  22.0  2017-01-29    E   其他    否  26  男   \n",
      "327278   32733781   2000    12  22.0  2017-01-29    E   其他    否  29  男   \n",
      "327288   32735611   6800    12  22.0  2017-01-29    E   其他    否  36  男   \n",
      "327307   32738121   2493    12  22.0  2017-01-30    E   其他    否  31  男   \n",
      "327395   32742761   2471    12  22.0  2017-01-30    E   其他    否  41  男   \n",
      "327397   32742821   3778    12  22.0  2017-01-29    E   其他    否  22  男   \n",
      "327464   32746421   2019    12  22.0  2017-01-29    E   其他    否  25  男   \n",
      "327571   32753441   2000    12  22.0  2017-01-30    E   其他    否  24  女   \n",
      "327578   32754091   2901    12  22.0  2017-01-30    E   其他    否  27  男   \n",
      "327582   32754631   3300    12  22.0  2017-01-30    E   其他    否  28  男   \n",
      "327583   32754871   3839    12  22.0  2017-01-29    E   其他    否  32  男   \n",
      "327747   32763121   2190    12  22.0  2017-01-30    E   普通    否  28  男   \n",
      "328079   32788161   2299    12  22.0  2017-01-30    E   普通    否  34  男   \n",
      "328406   32807781   2000    12  22.0  2017-01-30    E   其他    否  27  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "2         ...      未成功认证  未成功认证  未成功认证  未成功认证        5  21894.0  11726.32   \n",
      "6         ...       成功认证  未成功认证  未成功认证  未成功认证       15  63989.0   6619.37   \n",
      "10        ...       成功认证  未成功认证  未成功认证  未成功认证       12  71701.0   8109.78   \n",
      "11        ...       成功认证  未成功认证  未成功认证  未成功认证       12  79566.0      0.00   \n",
      "12        ...       成功认证  未成功认证  未成功认证  未成功认证        7  39000.0      0.00   \n",
      "13        ...       成功认证  未成功认证   成功认证  未成功认证       12  54122.0   8388.58   \n",
      "31        ...       成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   1651.70   \n",
      "61        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   2283.25   \n",
      "62        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "71        ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "72        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   2283.25   \n",
      "94        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   2688.46   \n",
      "103       ...       成功认证  未成功认证  未成功认证  未成功认证        3   9200.0   4211.64   \n",
      "106       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0      0.00   \n",
      "116       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "121       ...      未成功认证  未成功认证  未成功认证  未成功认证        5  22448.0      0.00   \n",
      "128       ...       成功认证  未成功认证  未成功认证  未成功认证        4  13314.0   3363.63   \n",
      "129       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0   3400.78   \n",
      "131       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "144       ...      未成功认证  未成功认证  未成功认证  未成功认证        3  11012.0   5479.35   \n",
      "172       ...       成功认证  未成功认证  未成功认证  未成功认证        5  17500.0   6233.32   \n",
      "176       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   9734.0   5173.56   \n",
      "180       ...       成功认证  未成功认证  未成功认证  未成功认证        2   7909.0      0.00   \n",
      "203       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7100.0   3245.92   \n",
      "216       ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "253       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "255       ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0   1548.38   \n",
      "283       ...       成功认证  未成功认证  未成功认证  未成功认证        3  10950.0      0.00   \n",
      "293       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "300       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "326625    ...      未成功认证  未成功认证  未成功认证  未成功认证        6  16111.0   6913.07   \n",
      "326700    ...      未成功认证   成功认证  未成功认证  未成功认证        1   9300.0   7161.49   \n",
      "326756    ...      未成功认证   成功认证  未成功认证  未成功认证        3   8800.0   6045.61   \n",
      "326790    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5159.0   3035.06   \n",
      "326828    ...      未成功认证   成功认证  未成功认证  未成功认证        1   9300.0   7161.49   \n",
      "326838    ...      未成功认证   成功认证  未成功认证  未成功认证        1   1000.0    532.09   \n",
      "326869    ...       成功认证   成功认证  未成功认证  未成功认证        7  14600.0   9727.42   \n",
      "326883    ...      未成功认证   成功认证  未成功认证  未成功认证        1  10000.0   7700.52   \n",
      "326949    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1800.0    470.38   \n",
      "326975    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  11500.0   5000.00   \n",
      "326986    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   8948.0   5249.48   \n",
      "327000    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7804.0   5804.00   \n",
      "327004    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  16880.0   8235.19   \n",
      "327063    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5397.0   2496.28   \n",
      "327106    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1900.0    962.99   \n",
      "327144    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2500.0   1348.46   \n",
      "327195    ...       成功认证  未成功认证  未成功认证  未成功认证        5  15369.0   7352.33   \n",
      "327278    ...      未成功认证   成功认证  未成功认证  未成功认证        1   6500.0   4488.73   \n",
      "327288    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5500.0   3647.22   \n",
      "327307    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0    506.84   \n",
      "327395    ...      未成功认证  未成功认证  未成功认证  未成功认证        6  17885.0   9820.26   \n",
      "327397    ...      未成功认证   成功认证  未成功认证  未成功认证        2   3030.0   1721.64   \n",
      "327464    ...      未成功认证   成功认证  未成功认证  未成功认证        8  25740.0  10580.89   \n",
      "327571    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   6000.0   4441.98   \n",
      "327578    ...      未成功认证   成功认证  未成功认证  未成功认证        1   9000.0   6098.62   \n",
      "327582    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2500.0   1699.59   \n",
      "327583    ...      未成功认证   成功认证  未成功认证  未成功认证        1   1500.0    760.27   \n",
      "327747    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4600.0   2310.15   \n",
      "328079    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9833.0   6201.49   \n",
      "328406    ...      未成功认证   成功认证  未成功认证  未成功认证        2   5400.0   2983.39   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "2             25         3  10.714286  \n",
      "6             75         8   9.638554  \n",
      "10            82         0   0.000000  \n",
      "11            82         0   0.000000  \n",
      "12            27         1   3.571429  \n",
      "13            34         0   0.000000  \n",
      "31             8         5  38.461538  \n",
      "61             3         0   0.000000  \n",
      "62             4         0   0.000000  \n",
      "71             4         0   0.000000  \n",
      "72             3         0   0.000000  \n",
      "94             6         0   0.000000  \n",
      "103           14         0   0.000000  \n",
      "106            7         1  12.500000  \n",
      "116            2         2  50.000000  \n",
      "121           25         2   7.407407  \n",
      "128           25         0   0.000000  \n",
      "129            6         0   0.000000  \n",
      "131            4         0   0.000000  \n",
      "144           12         0   0.000000  \n",
      "172           18         1   5.263158  \n",
      "176           10         0   0.000000  \n",
      "180            3         0   0.000000  \n",
      "203            6         0   0.000000  \n",
      "216            3         0   0.000000  \n",
      "253            2         0   0.000000  \n",
      "255            2         4  66.666667  \n",
      "283            7         0   0.000000  \n",
      "293            1         2  66.666667  \n",
      "300            4         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "326625        25         2   7.407407  \n",
      "326700         3         0   0.000000  \n",
      "326756        12         0   0.000000  \n",
      "326790         9         0   0.000000  \n",
      "326828         3         0   0.000000  \n",
      "326838         6         0   0.000000  \n",
      "326869        20        15  42.857143  \n",
      "326883         3         0   0.000000  \n",
      "326949         9         0   0.000000  \n",
      "326975         9         0   0.000000  \n",
      "326986        12         0   0.000000  \n",
      "327000        12         0   0.000000  \n",
      "327004        24         1   4.000000  \n",
      "327063        13         0   0.000000  \n",
      "327106         1         2  66.666667  \n",
      "327144         4         2  33.333333  \n",
      "327195        25         7  21.875000  \n",
      "327278         4         0   0.000000  \n",
      "327288         6         0   0.000000  \n",
      "327307         3         0   0.000000  \n",
      "327395        26         2   7.142857  \n",
      "327397         8         0   0.000000  \n",
      "327464        47         5   9.615385  \n",
      "327571        12         1   7.692308  \n",
      "327578         1         1  50.000000  \n",
      "327582         4         0   0.000000  \n",
      "327583         3         0   0.000000  \n",
      "327747        14         1   6.666667  \n",
      "328079        13         0   0.000000  \n",
      "328406        11         1   8.333333  \n",
      "\n",
      "[6171 rows x 22 columns],         ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别  \\\n",
      "18        1536991   3885    12  24.0  2015-01-04    F   普通    否  47  女   \n",
      "19        1537191   3228    12  24.0  2015-01-02    F   普通    否  39  男   \n",
      "20        1537391   5161    12  24.0  2015-01-02    F   普通    否  35  男   \n",
      "46        1557141   3500    12  24.0  2015-01-04    F   普通    否  32  男   \n",
      "127       1600291   4500    12  24.0  2015-01-07    F   普通    否  31  男   \n",
      "167       1618201   3000    12  24.0  2015-01-06    F   普通    否  41  男   \n",
      "182       1628371   3702    12  24.0  2015-01-08    F   普通    否  25  男   \n",
      "201       1633051   4189    12  24.0  2015-01-09    F   普通    否  25  男   \n",
      "242       1651171   3000    12  24.0  2015-01-16    F   普通    否  28  男   \n",
      "243       1651311   3179    12  24.0  2015-01-16    F   普通    否  26  男   \n",
      "277       1667721   4000    12  24.0  2015-01-17    F   普通    否  29  女   \n",
      "299       1673191   3200    12  24.0  2015-01-16    F   普通    否  42  男   \n",
      "309       1675891  11313    12  24.0  2015-01-14    F   其他    否  27  男   \n",
      "357       1689181   3672    12  24.0  2015-01-17    F   普通    否  28  男   \n",
      "365       1691151   3315    12  24.0  2015-01-19    F   普通    否  24  男   \n",
      "387       1696521   9000    12  24.0  2015-01-22    F   普通    否  36  男   \n",
      "402       1703601   3328    12  24.0  2015-01-21    F   普通    否  32  男   \n",
      "417       1706651   4500    12  24.0  2015-01-21    F   普通    否  29  男   \n",
      "445       1715541   5042    12  24.0  2015-01-28    F   普通    否  24  男   \n",
      "459       1717721   4200    12  24.0  2015-01-22    F   普通    否  24  男   \n",
      "479       1722281   3000     7  24.0  2015-01-23    F   普通    否  31  女   \n",
      "505       1728821   3222    12  24.0  2015-01-27    F   普通    否  29  男   \n",
      "545       1742581   4786    12  24.0  2015-01-28    F   普通    否  27  男   \n",
      "562       1748021   3500    12  24.0  2015-02-04    F   普通    否  25  男   \n",
      "605       1758361   3326    12  24.0  2015-02-02    F   普通    否  27  男   \n",
      "628       1767851   5000    12  24.0  2015-02-03    F   普通    否  33  男   \n",
      "630       1769061   3945    12  24.0  2015-02-03    F   普通    否  32  男   \n",
      "671       1783701   4474    12  24.0  2015-02-05    F   普通    否  25  男   \n",
      "674       1784451   4274    12  22.0  2015-02-09    F   普通    否  27  男   \n",
      "682       1785501   3300    12  24.0  2015-02-04    F   普通    否  30  女   \n",
      "...           ...    ...   ...   ...         ...  ...  ...  ...  .. ..   \n",
      "324215   32517371   2074    12  22.0  2017-01-25    F   其他    否  29  男   \n",
      "324290   32522281   2544    12  22.0  2017-01-25    F   其他    否  30  女   \n",
      "324357   32527131   2800     6  20.0  2017-01-25    F   其他    否  30  男   \n",
      "324579   32544591   2421    12  22.0  2017-01-25    F   其他    否  35  男   \n",
      "325081   32582431   2103     6  20.0  2017-01-28    F   其他    否  36  男   \n",
      "325211   32592201   2100    12  22.0  2017-01-26    F   其他    否  38  男   \n",
      "325251   32595231   2215    12  22.0  2017-01-26    F   其他    否  30  男   \n",
      "325320   32599441   2841    12  22.0  2017-01-26    F   其他    否  36  男   \n",
      "325392   32604251   2189    12  22.0  2017-01-26    F   其他    否  38  男   \n",
      "325555   32613921   2124    12  22.0  2017-01-26    F   其他    否  26  女   \n",
      "325581   32615381   4526    12  22.0  2017-01-26    F   普通    否  43  女   \n",
      "325650   32620361   2057    12  22.0  2017-01-26    F   其他    否  42  男   \n",
      "325985   32650791   9035    12  22.0  2017-01-27    F   普通    否  39  男   \n",
      "326037   32653491   4000    12  22.0  2017-01-27    F   其他    否  22  男   \n",
      "326070   32655291   2364    12  22.0  2017-01-27    F   普通    否  36  男   \n",
      "326197   32663941   2500    12  22.0  2017-01-27    F   其他    否  50  男   \n",
      "326690   32697991   2200    12  22.0  2017-01-28    F   其他    否  24  男   \n",
      "326709   32699231   2100    12  22.0  2017-01-28    F   其他    否  46  男   \n",
      "326977   32714371   4376    12  22.0  2017-01-28    F   其他    否  34  男   \n",
      "327301   32737141   2636    12  22.0  2017-01-29    F   其他    否  31  男   \n",
      "327306   32738101   2149    12  22.0  2017-01-29    F   其他    否  31  男   \n",
      "327381   32742161   4037    12  22.0  2017-01-29    F   其他    否  34  男   \n",
      "327389   32742571   2867    12  20.0  2017-01-29    F   其他    否  30  女   \n",
      "327390   32742621   1000    12  22.0  2017-01-29    F   普通    否  23  男   \n",
      "327518   32749901   3303    12  22.0  2017-01-29    F   普通    否  28  女   \n",
      "327623   32757621   5942    12  22.0  2017-01-30    F   普通    否  32  男   \n",
      "327811   32767661   3870    12  22.0  2017-01-30    F   其他    否  29  男   \n",
      "327819   32768451   2071    12  22.0  2017-01-30    F   其他    否  33  女   \n",
      "327945   32778951   2000    12  22.0  2017-01-30    F   其他    否  34  男   \n",
      "327968   32782241   2332    12  22.0  2017-01-30    F   其他    否  51  女   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "18        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   3827.98   \n",
      "19        ...      未成功认证  未成功认证  未成功认证  未成功认证        7  31100.0   7942.98   \n",
      "20        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10128.0   3284.98   \n",
      "46        ...       成功认证  未成功认证  未成功认证  未成功认证        5  16000.0   7757.39   \n",
      "127       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1297.26   \n",
      "167       ...       成功认证  未成功认证  未成功认证  未成功认证        3  10574.0      0.00   \n",
      "182       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "201       ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1297.26   \n",
      "242       ...      未成功认证   成功认证  未成功认证  未成功认证        4  12500.0   5466.05   \n",
      "243       ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "277       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0      0.00   \n",
      "299       ...      未成功认证  未成功认证  未成功认证  未成功认证        3  11719.0   5488.46   \n",
      "309       ...      未成功认证  未成功认证  未成功认证  未成功认证        3  12600.0   6692.78   \n",
      "357       ...      未成功认证   成功认证  未成功认证  未成功认证        3   9329.0   2195.89   \n",
      "365       ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10997.0   2795.45   \n",
      "387       ...       成功认证  未成功认证  未成功认证  未成功认证        8  35266.0      0.00   \n",
      "402       ...       成功认证   成功认证  未成功认证  未成功认证        2   6200.0   2399.36   \n",
      "417       ...       成功认证  未成功认证  未成功认证  未成功认证        6  32200.0   9306.29   \n",
      "445       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6339.0   2250.71   \n",
      "459       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "479       ...       成功认证  未成功认证  未成功认证  未成功认证        2   6000.0      0.00   \n",
      "505       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0   2078.10   \n",
      "545       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0    880.34   \n",
      "562       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "605       ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "628       ...       成功认证  未成功认证  未成功认证  未成功认证        3  11800.0      0.00   \n",
      "630       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "671       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6702.0      0.00   \n",
      "674       ...      未成功认证  未成功认证  未成功认证  未成功认证        5  18125.0   5714.37   \n",
      "682       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0      0.00   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "324215    ...      未成功认证   成功认证  未成功认证  未成功认证        1   1100.0    925.67   \n",
      "324290    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9470.0   5205.22   \n",
      "324357    ...       成功认证   成功认证  未成功认证  未成功认证       14  55780.0  17909.30   \n",
      "324579    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9000.0   6400.96   \n",
      "325081    ...      未成功认证   成功认证  未成功认证  未成功认证        8  28335.0   8518.87   \n",
      "325211    ...      未成功认证  未成功认证  未成功认证  未成功认证        5   9493.0   5395.86   \n",
      "325251    ...      未成功认证  未成功认证   成功认证  未成功认证        4   8259.0   4184.08   \n",
      "325320    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  11282.0   5658.26   \n",
      "325392    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  12621.0   8410.96   \n",
      "325555    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1700.0    875.35   \n",
      "325581    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  13361.0   5474.29   \n",
      "325650    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  15122.0   6442.37   \n",
      "325985    ...       成功认证  未成功认证  未成功认证  未成功认证        5  24111.0    882.21   \n",
      "326037    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9800.0   4456.73   \n",
      "326070    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10323.0   5635.89   \n",
      "326197    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   8000.0   6713.52   \n",
      "326690    ...       成功认证  未成功认证  未成功认证  未成功认证        3   8000.0   5770.68   \n",
      "326709    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  22657.0  15827.44   \n",
      "326977    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  13632.0   5123.23   \n",
      "327301    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4500.0   1863.88   \n",
      "327306    ...      未成功认证   成功认证  未成功认证  未成功认证        1   6200.0   4170.94   \n",
      "327381    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   6744.0   2962.93   \n",
      "327389    ...      未成功认证   成功认证  未成功认证  未成功认证        3   8724.0   5132.99   \n",
      "327390    ...       成功认证   成功认证  未成功认证  未成功认证        3   5138.0   2733.50   \n",
      "327518    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6546.0   3697.11   \n",
      "327623    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10470.0   3057.71   \n",
      "327811    ...      未成功认证  未成功认证  未成功认证  未成功认证       14  45616.0  12802.57   \n",
      "327819    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10240.0   6428.15   \n",
      "327945    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   8325.0   6065.42   \n",
      "327968    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  19955.0   9167.33   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "18             4         2  33.333333  \n",
      "19            12         9  42.857143  \n",
      "20            17         9  34.615385  \n",
      "46            16        11  40.740741  \n",
      "127            4         3  42.857143  \n",
      "167            5         2  28.571429  \n",
      "182            1         0   0.000000  \n",
      "201            5         2  28.571429  \n",
      "242           14         6  30.000000  \n",
      "243            1         6  85.714286  \n",
      "277            1        11  91.666667  \n",
      "299           13         3  18.750000  \n",
      "309            8         4  33.333333  \n",
      "357            8         0   0.000000  \n",
      "365            8         0   0.000000  \n",
      "387           15         9  37.500000  \n",
      "402            6         5  45.454545  \n",
      "417           19         2   9.523810  \n",
      "445           10         6  37.500000  \n",
      "459            8         4  33.333333  \n",
      "479            3        10  76.923077  \n",
      "505            9         0   0.000000  \n",
      "545            3         2  40.000000  \n",
      "562            3         4  57.142857  \n",
      "605            4         3  42.857143  \n",
      "628            8         2  20.000000  \n",
      "630            2         2  50.000000  \n",
      "671            2         0   0.000000  \n",
      "674           11         0   0.000000  \n",
      "682            3         4  57.142857  \n",
      "...          ...       ...        ...  \n",
      "324215         2         0   0.000000  \n",
      "324290        15         0   0.000000  \n",
      "324357        74         0   0.000000  \n",
      "324579         7         0   0.000000  \n",
      "325081        28         0   0.000000  \n",
      "325211        30         0   0.000000  \n",
      "325251        29         0   0.000000  \n",
      "325320        14         0   0.000000  \n",
      "325392         8         0   0.000000  \n",
      "325555         4         2  33.333333  \n",
      "325581        15         1   6.250000  \n",
      "325650        23         0   0.000000  \n",
      "325985        53         0   0.000000  \n",
      "326037        16         0   0.000000  \n",
      "326070        16         0   0.000000  \n",
      "326197         6         0   0.000000  \n",
      "326690        11         0   0.000000  \n",
      "326709        10         0   0.000000  \n",
      "326977        31         2   6.060606  \n",
      "327301        17         0   0.000000  \n",
      "327306         1         1  50.000000  \n",
      "327381         9         0   0.000000  \n",
      "327389         9         3  25.000000  \n",
      "327390        18         0   0.000000  \n",
      "327518        11         0   0.000000  \n",
      "327623         9         3  25.000000  \n",
      "327811        91         1   1.086957  \n",
      "327819        12         0   0.000000  \n",
      "327945         9         0   0.000000  \n",
      "327968        28         1   3.448276  \n",
      "\n",
      "[864 rows x 22 columns]]\n"
     ]
    }
   ],
   "source": [
    "level_idx=('A','B','C','D','E','F')\n",
    "lev=[]\n",
    "for i in level_idx:\n",
    "    temp = LC[LC['初始评级'] == i]\n",
    "    lev.append(temp)\n",
    "print(lev)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 借款类型的数据划分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:38:04.768451Z",
     "start_time": "2020-07-30T13:38:04.381674Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[        ListingId    借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别  \\\n",
      "4          152141   20000     6  16.0  2015-01-22    C   电商    否  24  男   \n",
      "6          171191    3940     6  18.0  2015-06-26    E   电商    否  27  女   \n",
      "9          193831   10475     6  18.0  2015-04-15    C   电商    否  25  男   \n",
      "15        1080421    5250     6  18.0  2015-05-27    C   电商    否  25  男   \n",
      "43        1553501  400000     6  14.0  2015-01-03    B   电商    否  44  女   \n",
      "76        1578401  460000     6  14.0  2015-01-04    B   电商    否  38  男   \n",
      "81        1579591    4311    10  20.0  2015-01-04    C   电商    否  27  女   \n",
      "114       1594791    5200     6  18.0  2015-01-05    C   电商    否  31  男   \n",
      "140       1606911   54000     6  15.0  2015-01-05    B   电商    否  28  男   \n",
      "187       1629111    4420     6  16.0  2015-01-07    C   电商    否  25  女   \n",
      "198       1631971   30000     6  16.0  2015-01-20    C   电商    否  31  男   \n",
      "220       1642311   20000     6  16.0  2015-01-09    C   电商    否  29  男   \n",
      "228       1644011   40000     6  16.0  2015-01-12    B   电商    否  31  男   \n",
      "257       1661461  229000     6  16.0  2015-01-13    B   电商    否  36  男   \n",
      "259       1661961    3000     3  20.0  2015-01-16    C   电商    否  31  男   \n",
      "285       1669341   30400     6  16.0  2015-01-14    C   电商    否  33  男   \n",
      "288       1671211   40000     6  16.0  2015-01-15    C   电商    否  25  男   \n",
      "310       1676381   10000     6  16.0  2015-01-16    C   电商    否  34  女   \n",
      "313       1677551   50000     6  15.0  2015-01-18    B   电商    否  33  男   \n",
      "336       1683171    4484    12  20.0  2015-01-19    C   电商    否  34  男   \n",
      "380       1694511    8800     3  20.0  2015-01-20    C   电商    否  28  男   \n",
      "434       1711831    8000     6  18.0  2015-01-23    C   电商    否  24  男   \n",
      "443       1715151   20000     6  16.0  2015-01-22    C   电商    否  44  男   \n",
      "470       1721161  156000     6  16.0  2015-01-30    B   电商    否  28  男   \n",
      "494       1727531   50000     6  16.0  2015-01-27    C   电商    否  27  男   \n",
      "536       1740571    5400     6  18.0  2015-05-26    C   电商    否  28  男   \n",
      "580       1751561  200000     6  16.0  2015-02-06    B   电商    否  39  男   \n",
      "582       1751631  165000     6  14.0  2015-02-10    B   电商    否  32  男   \n",
      "660       1779221   23500     6  18.0  2015-02-03    C   电商    否  35  女   \n",
      "691       1789491   35000     6  16.0  2015-02-06    C   电商    否  45  女   \n",
      "...           ...     ...   ...   ...         ...  ...  ...  ...  .. ..   \n",
      "197218   22512521  296000     6  18.0  2016-10-19    B   电商    否  30  男   \n",
      "197536   22538851  145500     6  16.0  2016-10-20    B   电商    否  39  男   \n",
      "197656   22545271  171000     6  15.0  2016-10-22    B   电商    否  40  女   \n",
      "198358   22602601   30000     6  18.0  2016-10-20    C   电商    否  45  男   \n",
      "199540   22695681    3256     6  18.0  2016-10-21    C   电商    否  37  男   \n",
      "199542   22695801   40000     6  18.0  2016-10-21    B   电商    否  32  男   \n",
      "199891   22720471   17669     6  18.0  2016-10-21    C   电商    否  26  男   \n",
      "199905   22721221   21000     6  18.0  2016-10-21    C   电商    否  32  男   \n",
      "202749   22932831   14442     6  18.0  2016-10-24    C   电商    否  48  女   \n",
      "204524   23064331   88200     6  16.0  2016-10-25    B   电商    否  35  男   \n",
      "205557   23144121  243300     6  14.0  2016-10-27    B   电商    否  36  男   \n",
      "205628   23147821   50000     6  18.0  2016-10-26    B   电商    否  34  男   \n",
      "210722   23534931   40000     6  18.0  2016-10-31    B   电商    否  32  男   \n",
      "210897   23546491  260000     3  14.0  2016-10-31    B   电商    否  41  女   \n",
      "210955   23551121   36166     6  14.0  2016-11-01    C   电商    否  33  男   \n",
      "211210   23566851  160000     6  13.0  2016-10-31    B   电商    否  33  女   \n",
      "213467   23740951  124500     6  15.0  2016-11-03    B   电商    否  28  男   \n",
      "215660   23922621    5283     6  18.0  2016-11-07    C   电商    否  29  男   \n",
      "215772   23932071   10000     6  18.0  2016-11-04    C   电商    否  42  男   \n",
      "219931   24292141  118000     6  15.0  2016-11-09    B   电商    否  30  男   \n",
      "222821   24519361   20000     6  18.0  2016-11-16    C   电商    否  36  男   \n",
      "231541   25186611   50000     6  18.0  2016-11-18    B   电商    否  41  男   \n",
      "234388   25410231  146716     6  14.0  2016-11-21    B   电商    否  26  男   \n",
      "243305   26075771  150300     6  14.0  2016-11-28    B   电商    否  39  男   \n",
      "248655   26431171   25586     6  14.0  2016-12-02    C   电商    否  41  女   \n",
      "249740   26507481   20000     6  18.0  2016-12-02    C   电商    否  33  男   \n",
      "256593   26969571   40000     6  15.0  2016-12-07    B   电商    否  32  男   \n",
      "263432   27437311   10310     6  14.0  2016-12-12    C   电商    否  26  男   \n",
      "281590   28887471  100000     3  14.0  2016-12-27    B   电商    否  29  男   \n",
      "282690   28984491  100000     6  14.0  2016-12-27    B   电商    否  21  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数   历史成功借款金额       总待还本金  \\\n",
      "4         ...       成功认证  未成功认证  未成功认证  未成功认证       13    77945.0        0.00   \n",
      "6         ...       成功认证  未成功认证  未成功认证  未成功认证       15    63989.0     6619.37   \n",
      "9         ...       成功认证  未成功认证  未成功认证  未成功认证        9   107000.0        0.00   \n",
      "15        ...       成功认证  未成功认证  未成功认证   成功认证        7   379000.0    10745.88   \n",
      "43        ...       成功认证  未成功认证  未成功认证  未成功认证        1   350000.0        0.00   \n",
      "76        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   400000.0        0.00   \n",
      "81        ...      未成功认证  未成功认证  未成功认证  未成功认证        2     6147.0     3012.83   \n",
      "114       ...       成功认证  未成功认证  未成功认证  未成功认证       15    85490.0     6715.80   \n",
      "140       ...       成功认证   成功认证  未成功认证  未成功认证        1    90000.0    45893.93   \n",
      "187       ...       成功认证  未成功认证  未成功认证  未成功认证        2    13290.0     3573.17   \n",
      "198       ...       成功认证  未成功认证  未成功认证  未成功认证        1    20000.0        0.00   \n",
      "220       ...       成功认证  未成功认证  未成功认证  未成功认证        2    20000.0        0.00   \n",
      "228       ...       成功认证  未成功认证  未成功认证  未成功认证        3   124500.0        0.00   \n",
      "257       ...       成功认证  未成功认证  未成功认证  未成功认证        3   797000.0   100456.72   \n",
      "259       ...      未成功认证  未成功认证  未成功认证  未成功认证        1     3000.0     2019.84   \n",
      "285       ...       成功认证   成功认证  未成功认证  未成功认证        2    21700.0     9547.26   \n",
      "288       ...       成功认证  未成功认证  未成功认证  未成功认证        1    30000.0        0.00   \n",
      "310       ...       成功认证  未成功认证  未成功认证  未成功认证        1    10000.0        0.00   \n",
      "313       ...       成功认证   成功认证  未成功认证  未成功认证        1    40000.0        0.00   \n",
      "336       ...       成功认证  未成功认证  未成功认证  未成功认证        4    13443.0     4979.89   \n",
      "380       ...       成功认证  未成功认证  未成功认证  未成功认证        4    17270.0        0.00   \n",
      "434       ...       成功认证  未成功认证  未成功认证  未成功认证        1     6000.0        0.00   \n",
      "443       ...       成功认证  未成功认证  未成功认证  未成功认证        1    40000.0        0.00   \n",
      "470       ...       成功认证  未成功认证  未成功认证  未成功认证        2   373000.0   113577.45   \n",
      "494       ...       成功认证   成功认证  未成功认证  未成功认证        1    10000.0        0.00   \n",
      "536       ...       成功认证   成功认证  未成功认证   成功认证        8    52000.0    14504.72   \n",
      "580       ...       成功认证  未成功认证  未成功认证  未成功认证        2   550000.0        0.00   \n",
      "582       ...       成功认证  未成功认证  未成功认证  未成功认证        1   200000.0    34377.04   \n",
      "660       ...       成功认证   成功认证  未成功认证  未成功认证        4    70000.0        0.00   \n",
      "691       ...       成功认证  未成功认证  未成功认证  未成功认证        2    66300.0     4529.76   \n",
      "...       ...        ...    ...    ...    ...      ...        ...         ...   \n",
      "197218    ...       成功认证  未成功认证  未成功认证   成功认证        3  1056000.0   555575.36   \n",
      "197536    ...       成功认证  未成功认证  未成功认证   成功认证        4   291161.0    63108.49   \n",
      "197656    ...       成功认证  未成功认证  未成功认证   成功认证        4   602800.0   168728.30   \n",
      "198358    ...       成功认证  未成功认证  未成功认证   成功认证        4   441217.0        0.00   \n",
      "199540    ...       成功认证   成功认证  未成功认证   成功认证        1    10000.0     6743.70   \n",
      "199542    ...       成功认证  未成功认证  未成功认证   成功认证       10   116180.0        0.00   \n",
      "199891    ...       成功认证   成功认证   成功认证   成功认证        1    38000.0    19330.55   \n",
      "199905    ...       成功认证  未成功认证   成功认证   成功认证        4   402300.0    49945.23   \n",
      "202749    ...       成功认证  未成功认证  未成功认证   成功认证        2   210000.0    25558.22   \n",
      "204524    ...       成功认证   成功认证   成功认证   成功认证        1   180000.0    91787.85   \n",
      "205557    ...       成功认证   成功认证  未成功认证  未成功认证        4  1369000.0   519887.69   \n",
      "205628    ...       成功认证  未成功认证   成功认证   成功认证        1    70000.0        0.00   \n",
      "210722    ...       成功认证   成功认证  未成功认证   成功认证        9  1030000.0        0.00   \n",
      "210897    ...       成功认证  未成功认证  未成功认证   成功认证        3  1174000.0   490714.80   \n",
      "210955    ...       成功认证  未成功认证   成功认证   成功认证        3   214500.0    47307.18   \n",
      "211210    ...       成功认证   成功认证  未成功认证   成功认证        8  2826000.0  1172652.87   \n",
      "213467    ...       成功认证   成功认证   成功认证   成功认证        6   569727.0    45436.49   \n",
      "215660    ...       成功认证  未成功认证  未成功认证   成功认证        7    98491.0     6716.95   \n",
      "215772    ...       成功认证  未成功认证   成功认证  未成功认证        1   170000.0        0.00   \n",
      "219931    ...       成功认证  未成功认证  未成功认证   成功认证        7  1695000.0   793011.46   \n",
      "222821    ...       成功认证  未成功认证  未成功认证   成功认证        6   430700.0    15297.99   \n",
      "231541    ...       成功认证  未成功认证   成功认证   成功认证        3   240000.0        0.00   \n",
      "234388    ...       成功认证  未成功认证  未成功认证   成功认证        7   666000.0   172964.54   \n",
      "243305    ...       成功认证  未成功认证  未成功认证   成功认证        7  1239000.0   253466.64   \n",
      "248655    ...       成功认证  未成功认证  未成功认证   成功认证        2   260000.0    88900.50   \n",
      "249740    ...       成功认证   成功认证  未成功认证   成功认证        4    80000.0     5133.02   \n",
      "256593    ...       成功认证  未成功认证  未成功认证   成功认证        2   450000.0    57986.21   \n",
      "263432    ...       成功认证  未成功认证  未成功认证   成功认证        2    81282.0    29689.51   \n",
      "281590    ...       成功认证  未成功认证  未成功认证   成功认证        8  2283000.0        0.00   \n",
      "282690    ...       成功认证   成功认证   成功认证  未成功认证        2   355000.0        0.00   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "4            118        14  10.606061  \n",
      "6             75         8   9.638554  \n",
      "9             49         4   7.547170  \n",
      "15            31         2   6.060606  \n",
      "43             6         0   0.000000  \n",
      "76             4         2  33.333333  \n",
      "81             7         0   0.000000  \n",
      "114           40         3   6.976744  \n",
      "140            3         0   0.000000  \n",
      "187            5         0   0.000000  \n",
      "198            5         1  16.666667  \n",
      "220            6         0   0.000000  \n",
      "228           14         1   6.666667  \n",
      "257           11         4  26.666667  \n",
      "259            2         0   0.000000  \n",
      "285           12         0   0.000000  \n",
      "288            6         0   0.000000  \n",
      "310            3         0   0.000000  \n",
      "313            6         0   0.000000  \n",
      "336           25         0   0.000000  \n",
      "380            8         0   0.000000  \n",
      "434            5         1  16.666667  \n",
      "443            6         0   0.000000  \n",
      "470            6         3  33.333333  \n",
      "494            6         0   0.000000  \n",
      "536           32         2   5.882353  \n",
      "580            9         0   0.000000  \n",
      "582            5         0   0.000000  \n",
      "660           21         0   0.000000  \n",
      "691           10         1   9.090909  \n",
      "...          ...       ...        ...  \n",
      "197218         8         0   0.000000  \n",
      "197536        20         0   0.000000  \n",
      "197656        20         0   0.000000  \n",
      "198358        23         1   4.166667  \n",
      "199540         2         0   0.000000  \n",
      "199542        91         2   2.150538  \n",
      "199891         3         0   0.000000  \n",
      "199905        18         1   5.263158  \n",
      "202749         9         0   0.000000  \n",
      "204524         3         0   0.000000  \n",
      "205557        14         0   0.000000  \n",
      "205628         6         0   0.000000  \n",
      "210722        22         0   0.000000  \n",
      "210897         9         0   0.000000  \n",
      "210955         9         2  18.181818  \n",
      "211210        32         0   0.000000  \n",
      "213467        31         3   8.823529  \n",
      "215660        37         1   2.631579  \n",
      "215772         6         0   0.000000  \n",
      "219931        24         0   0.000000  \n",
      "222821        32         1   3.030303  \n",
      "231541        18         0   0.000000  \n",
      "234388        25         1   3.846154  \n",
      "243305        31         0   0.000000  \n",
      "248655         5         3  37.500000  \n",
      "249740        22         0   0.000000  \n",
      "256593        10         0   0.000000  \n",
      "263432         7         0   0.000000  \n",
      "281590        23         2   8.000000  \n",
      "282690        12         0   0.000000  \n",
      "\n",
      "[765 rows x 22 columns],         ListingId  借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "12257     4432991  2000     6  18.0  2015-09-27    D  APP闪电    否  29  男   \n",
      "12391     4449091  1600     6  24.0  2015-09-28    D  APP闪电    否  29  男   \n",
      "12482     4460461  2000     3  18.0  2015-09-28    D  APP闪电    否  41  女   \n",
      "12511     4463121  2020     6  24.0  2015-09-28    D  APP闪电    否  36  男   \n",
      "12550     4472951  2000     3  18.0  2015-09-28    D  APP闪电    否  42  男   \n",
      "12563     4474141  1760     6  24.0  2015-09-28    D  APP闪电    否  25  男   \n",
      "12596     4477771  1000     3  18.0  2015-09-28    D  APP闪电    否  28  男   \n",
      "12663     4487671  2320     6  18.0  2015-09-29    D  APP闪电    否  42  男   \n",
      "12688     4492311  1600     6  24.0  2015-10-08    E  APP闪电    否  43  男   \n",
      "12745     4500491   860     6  18.0  2015-10-10    E  APP闪电    否  27  男   \n",
      "12754     4501891  2000     3  18.0  2015-10-07    E  APP闪电    否  39  男   \n",
      "12770     4504091  2180     6  18.0  2015-09-30    B  APP闪电    否  27  男   \n",
      "12793     4508381   442     6  18.0  2015-09-29    B  APP闪电    否  30  女   \n",
      "12801     4509371   330     3  18.0  2015-10-06    E  APP闪电    否  22  男   \n",
      "12816     4510791   900     6  18.0  2015-10-05    B  APP闪电    否  21  男   \n",
      "12982     4532931  2000     6  18.0  2015-10-03    B  APP闪电    否  24  男   \n",
      "13075     4542861  1050     6  18.0  2015-10-24    E  APP闪电    否  25  男   \n",
      "13122     4547251  1100     3  24.0  2015-10-10    E  APP闪电    否  27  男   \n",
      "13165     4557191  2000     3  18.0  2015-10-15    E  APP闪电    否  45  男   \n",
      "13195     4560501  2015     6  18.0  2015-10-24    E  APP闪电    否  25  女   \n",
      "13209     4561691  2010     6  18.0  2015-10-06    B  APP闪电    否  24  男   \n",
      "13218     4562711  1900     3  18.0  2015-10-06    B  APP闪电    否  42  男   \n",
      "13283     4569311  2000     3  18.0  2015-10-18    E  APP闪电    否  26  男   \n",
      "13307     4572191  2000     3  18.0  2015-10-18    E  APP闪电    否  28  男   \n",
      "13309     4572491  2100     3  18.0  2015-10-07    B  APP闪电    否  35  男   \n",
      "13347     4580981  1800     3  18.0  2015-10-08    B  APP闪电    否  33  男   \n",
      "13405     4589761  2200     6  18.0  2015-10-08    B  APP闪电    否  29  男   \n",
      "13411     4590551  1570     6  24.0  2015-10-18    E  APP闪电    否  30  女   \n",
      "13421     4593171  1500     6  24.0  2015-10-19    E  APP闪电    否  24  男   \n",
      "13475     4604041  1000     6  18.0  2015-10-09    B  APP闪电    否  28  男   \n",
      "...           ...   ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328471   32812331  1179    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "328472   32812341  1000    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328474   32812631  1581    12  22.0  2017-01-30    D  APP闪电    否  29  男   \n",
      "328476   32812671  1868     6  18.0  2017-01-30    B  APP闪电    否  32  男   \n",
      "328485   32813391   700    12  20.0  2017-01-30    C  APP闪电    否  23  女   \n",
      "328488   32813601  5089     6  20.0  2017-01-30    C  APP闪电    否  32  男   \n",
      "328489   32813661  2800    12  22.0  2017-01-30    D  APP闪电    否  32  男   \n",
      "328490   32813831  2885    12  18.0  2017-01-30    B  APP闪电    否  30  男   \n",
      "328492   32814071   955    12  22.0  2017-01-30    D  APP闪电    否  41  男   \n",
      "328494   32814141   995    12  18.0  2017-01-30    B  APP闪电    否  35  女   \n",
      "328496   32814211  1313    12  22.0  2017-01-30    D  APP闪电    否  27  男   \n",
      "328501   32814781  1556     6  18.0  2017-01-30    B  APP闪电    否  29  女   \n",
      "328504   32815111  4201    12  22.0  2017-01-30    D  APP闪电    否  45  男   \n",
      "328509   32815421  1396    12  22.0  2017-01-30    D  APP闪电    否  35  男   \n",
      "328510   32815471  2571    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328511   32815751   990    12  22.0  2017-01-30    D  APP闪电    否  36  男   \n",
      "328512   32815861  4000    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328513   32815871  3327    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328515   32816321   700    12  22.0  2017-01-30    D  APP闪电    否  22  女   \n",
      "328517   32816441  2500    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328522   32817131  3592    12  22.0  2017-01-30    D  APP闪电    否  31  女   \n",
      "328527   32817401  1200    12  20.0  2017-01-30    C  APP闪电    否  22  男   \n",
      "328531   32817811   730    12  22.0  2017-01-30    D  APP闪电    否  30  女   \n",
      "328534   32818011   728    12  20.0  2017-01-30    C  APP闪电    否  36  男   \n",
      "328535   32818041   782     6  20.0  2017-01-30    C  APP闪电    否  38  女   \n",
      "328536   32818051  1175    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328538   32818171  1677    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328540   32818411  1814    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328541   32818591  2067    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328546   32818911   782    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "12257     ...      未成功认证   成功认证  未成功认证  未成功认证        3   9455.0   5696.71   \n",
      "12391     ...      未成功认证  未成功认证  未成功认证  未成功认证        4   6970.0   5099.77   \n",
      "12482     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   2283.25   \n",
      "12511     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2250.0   1513.03   \n",
      "12550     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   2523.54   \n",
      "12563     ...      未成功认证  未成功认证  未成功认证  未成功认证        1    250.0      0.00   \n",
      "12596     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4000.0   2230.20   \n",
      "12663     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4250.0   2856.78   \n",
      "12688     ...      未成功认证  未成功认证  未成功认证  未成功认证        4  14874.0   7999.73   \n",
      "12745     ...      未成功认证  未成功认证   成功认证  未成功认证        4   7510.0   4624.26   \n",
      "12754     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7400.0   5920.54   \n",
      "12770     ...      未成功认证  未成功认证  未成功认证  未成功认证        3   5400.0   3586.92   \n",
      "12793     ...      未成功认证  未成功认证   成功认证  未成功认证        4   9711.0   7719.97   \n",
      "12801     ...      未成功认证  未成功认证   成功认证  未成功认证        4   4890.0   4404.40   \n",
      "12816     ...      未成功认证   成功认证  未成功认证  未成功认证        2   1240.0   1041.99   \n",
      "12982     ...      未成功认证   成功认证  未成功认证  未成功认证        5  25727.0   9500.24   \n",
      "13075     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   2691.78   \n",
      "13122     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   3390.0   1910.54   \n",
      "13165     ...      未成功认证   成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "13195     ...      未成功认证   成功认证  未成功认证  未成功认证        1   8000.0   6729.42   \n",
      "13209     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   3981.0   2177.11   \n",
      "13218     ...      未成功认证  未成功认证  未成功认证  未成功认证        3   5815.0   3744.54   \n",
      "13283     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4500.0      0.00   \n",
      "13307     ...      未成功认证   成功认证  未成功认证  未成功认证        1   5000.0   3362.30   \n",
      "13309     ...      未成功认证   成功认证  未成功认证  未成功认证        1   3500.0   2353.61   \n",
      "13347     ...      未成功认证  未成功认证  未成功认证  未成功认证        1    500.0      0.00   \n",
      "13405     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   3910.0   2129.60   \n",
      "13411     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4250.0   3575.01   \n",
      "13421     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2500.0   2102.95   \n",
      "13475     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   3220.0   2259.54   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "328471    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   7728.0   4320.62   \n",
      "328472    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1200.0      0.00   \n",
      "328474    ...      未成功认证  未成功认证  未成功认证  未成功认证        8  16526.0   8218.49   \n",
      "328476    ...      未成功认证   成功认证  未成功认证  未成功认证        2  11000.0   6131.95   \n",
      "328485    ...      未成功认证   成功认证  未成功认证  未成功认证        6   6953.0   5282.08   \n",
      "328488    ...      未成功认证   成功认证  未成功认证  未成功认证        1   7000.0   2410.89   \n",
      "328489    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  10667.0   3993.59   \n",
      "328490    ...      未成功认证   成功认证  未成功认证  未成功认证        6  15091.0   7514.90   \n",
      "328492    ...      未成功认证   成功认证  未成功认证  未成功认证        1   4000.0   3044.33   \n",
      "328494    ...      未成功认证   成功认证  未成功认证  未成功认证       10  14882.0   6704.93   \n",
      "328496    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5500.0   3786.48   \n",
      "328501    ...      未成功认证   成功认证  未成功认证  未成功认证        5  16812.0   9743.68   \n",
      "328504    ...      未成功认证  未成功认证  未成功认证  未成功认证        2  10500.0   6098.62   \n",
      "328509    ...      未成功认证  未成功认证  未成功认证  未成功认证       11  16254.0   6303.57   \n",
      "328510    ...      未成功认证  未成功认证  未成功认证  未成功认证       10  16548.0   6328.08   \n",
      "328511    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1500.0    509.15   \n",
      "328512    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4000.0      0.00   \n",
      "328513    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0    672.73   \n",
      "328515    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   2250.0    749.35   \n",
      "328517    ...      未成功认证   成功认证  未成功认证  未成功认证        3   2000.0   1438.58   \n",
      "328522    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3107.58   \n",
      "328527    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1750.0    603.74   \n",
      "328531    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5426.0   2969.05   \n",
      "328534    ...      未成功认证   成功认证  未成功认证  未成功认证        7  10948.0   6271.30   \n",
      "328535    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  14691.0  10087.86   \n",
      "328536    ...       成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3424.88   \n",
      "328538    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   4805.0   2422.66   \n",
      "328540    ...      未成功认证   成功认证  未成功认证  未成功认证        2   5000.0   2885.30   \n",
      "328541    ...      未成功认证   成功认证  未成功认证  未成功认证        2   3993.0   3332.43   \n",
      "328546    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4818.0   3217.74   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "12257         15         0   0.000000  \n",
      "12391          7         2  22.222222  \n",
      "12482          3         0   0.000000  \n",
      "12511          2         0   0.000000  \n",
      "12550          2         0   0.000000  \n",
      "12563          2         0   0.000000  \n",
      "12596          5         0   0.000000  \n",
      "12663          2         0   0.000000  \n",
      "12688         11         1   8.333333  \n",
      "12745          8         3  27.272727  \n",
      "12754          3         0   0.000000  \n",
      "12770          4         4  50.000000  \n",
      "12793          7         0   0.000000  \n",
      "12801          3         0   0.000000  \n",
      "12816          2         0   0.000000  \n",
      "12982         17         0   0.000000  \n",
      "13075          9         0   0.000000  \n",
      "13122          3         0   0.000000  \n",
      "13165          2         0   0.000000  \n",
      "13195          2         0   0.000000  \n",
      "13209          4         0   0.000000  \n",
      "13218          4         0   0.000000  \n",
      "13283          6         0   0.000000  \n",
      "13307          2         0   0.000000  \n",
      "13309          2         0   0.000000  \n",
      "13347          3         0   0.000000  \n",
      "13405          4         0   0.000000  \n",
      "13411          2         0   0.000000  \n",
      "13421          2         0   0.000000  \n",
      "13475          3         1  25.000000  \n",
      "...          ...       ...        ...  \n",
      "328471         7         0   0.000000  \n",
      "328472         6         0   0.000000  \n",
      "328474        27         0   0.000000  \n",
      "328476         9         0   0.000000  \n",
      "328485        17         0   0.000000  \n",
      "328488         4         0   0.000000  \n",
      "328489        18         0   0.000000  \n",
      "328490        31         0   0.000000  \n",
      "328492         3         0   0.000000  \n",
      "328494        52         0   0.000000  \n",
      "328496         4         0   0.000000  \n",
      "328501        20         0   0.000000  \n",
      "328504         8         0   0.000000  \n",
      "328509        52         0   0.000000  \n",
      "328510        45         0   0.000000  \n",
      "328511         3         1  25.000000  \n",
      "328512         6         0   0.000000  \n",
      "328513         2         0   0.000000  \n",
      "328515        24         2   7.692308  \n",
      "328517         8         0   0.000000  \n",
      "328522         4         0   0.000000  \n",
      "328527         8         0   0.000000  \n",
      "328531         5         0   0.000000  \n",
      "328534        28         0   0.000000  \n",
      "328535         7         0   0.000000  \n",
      "328536         3         0   0.000000  \n",
      "328538        10         0   0.000000  \n",
      "328540         7         0   0.000000  \n",
      "328541         4         0   0.000000  \n",
      "328546         4         1  20.000000  \n",
      "\n",
      "[80626 rows x 22 columns],         ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别  \\\n",
      "2          142421  27000    24  20.0  2016-04-26    E   普通    否  41  男   \n",
      "5          162641  20000    12  14.0  2015-03-25    A   普通    否  36  男   \n",
      "7          175451  20000    12  18.0  2016-03-19    B   普通    否  32  男   \n",
      "10         199461  25000    12  20.0  2015-11-29    E   普通    否  29  男   \n",
      "11         209191  20000    12  20.0  2015-11-28    E   普通    否  33  男   \n",
      "13         223081  26000    12  20.0  2016-06-28    E   普通    否  35  男   \n",
      "16        1518801   4913    12  24.0  2015-01-01    D   普通    否  26  男   \n",
      "18        1536991   3885    12  24.0  2015-01-04    F   普通    否  47  女   \n",
      "19        1537191   3228    12  24.0  2015-01-02    F   普通    否  39  男   \n",
      "20        1537391   5161    12  24.0  2015-01-02    F   普通    否  35  男   \n",
      "21        1537661   8000    12  20.0  2015-01-04    C   普通    否  39  男   \n",
      "22        1538211   3000    12  20.0  2015-01-04    D   普通    否  23  女   \n",
      "23        1540111  12778    12  20.0  2015-01-04    D   普通    否  26  男   \n",
      "24        1541631  10000    12  20.0  2015-01-04    D   普通    否  38  男   \n",
      "26        1541761  10000    12  20.0  2015-01-04    D   普通    否  29  男   \n",
      "27        1542581   3500    12  18.0  2015-01-04    C   普通    否  28  男   \n",
      "28        1542681  13083    12  18.0  2015-01-04    C   普通    否  46  男   \n",
      "29        1542821  11748    12  18.0  2015-01-04    C   普通    否  29  女   \n",
      "30        1546771  12000    12  18.0  2015-01-04    C   普通    否  27  男   \n",
      "31        1547751   3900    12  23.0  2015-01-04    E   普通    否  27  男   \n",
      "33        1548521  10053    12  18.0  2015-01-07    C   普通    否  34  男   \n",
      "35        1549891   4940    12  22.0  2015-01-02    C   普通    否  24  男   \n",
      "36        1550751   3500    12  20.0  2015-01-05    D   普通    否  27  男   \n",
      "37        1551201   3884    12  22.0  2015-01-05    D   普通    否  25  男   \n",
      "38        1551311   8500    12  20.0  2015-01-04    C   普通    否  31  男   \n",
      "39        1551331   4691    12  18.0  2015-01-04    B   普通    否  45  男   \n",
      "40        1551871   3500    12  21.0  2015-01-05    D   普通    否  23  男   \n",
      "41        1551961   8972    12  18.0  2015-01-06    C   普通    否  31  女   \n",
      "42        1553151   8000    12  18.0  2015-01-07    C   普通    否  36  男   \n",
      "44        1554311   9000     6  18.0  2015-01-04    D   普通    否  25  男   \n",
      "...           ...    ...   ...   ...         ...  ...  ...  ...  .. ..   \n",
      "328385   32806581   4842    12  20.0  2017-01-30    C   普通    否  23  男   \n",
      "328393   32807141   4402    12  22.0  2017-01-30    C   普通    否  24  男   \n",
      "328394   32807181   2054    11  20.0  2017-01-30    C   普通    否  44  男   \n",
      "328395   32807211   2000    10  20.0  2017-01-30    C   普通    否  25  男   \n",
      "328399   32807381   5982    12  20.0  2017-01-30    C   普通    否  38  女   \n",
      "328408   32807801   5051    12  20.0  2017-01-30    C   普通    否  27  男   \n",
      "328416   32808181   5482    12  22.0  2017-01-30    C   普通    否  29  男   \n",
      "328421   32808481   3782    12  22.0  2017-01-30    D   普通    否  30  女   \n",
      "328423   32808831   4000    12  22.0  2017-01-30    D   普通    否  25  男   \n",
      "328426   32808971   2000     6  20.0  2017-01-30    C   普通    否  31  男   \n",
      "328427   32809011   2416     6  20.0  2017-01-30    C   普通    否  23  男   \n",
      "328429   32809061   4931     6  20.0  2017-01-30    C   普通    否  25  男   \n",
      "328432   32809531   7133     3  16.0  2017-01-30    A   普通    否  38  女   \n",
      "328445   32810171   5500    12  22.0  2017-01-30    D   普通    否  34  男   \n",
      "328454   32810981   5630     6  20.0  2017-01-30    C   普通    否  34  女   \n",
      "328463   32811681   4180    12  22.0  2017-01-30    C   普通    否  35  男   \n",
      "328466   32811931   4202     9  20.0  2017-01-30    C   普通    否  33  女   \n",
      "328467   32811991   4565    12  22.0  2017-01-30    D   普通    否  33  男   \n",
      "328475   32812651   5089    12  20.0  2017-01-30    C   普通    否  28  男   \n",
      "328477   32812681   2482    12  22.0  2017-01-30    D   普通    否  28  男   \n",
      "328484   32813311   5803     6  20.0  2017-01-30    C   普通    否  47  男   \n",
      "328495   32814151   3900    12  20.0  2017-01-30    C   普通    否  22  男   \n",
      "328500   32814731   2696    12  20.0  2017-01-30    C   普通    否  41  男   \n",
      "328505   32815181   5000    12  22.0  2017-01-30    D   普通    否  41  男   \n",
      "328516   32816401   3548    12  20.0  2017-01-30    D   普通    否  38  男   \n",
      "328524   32817221   5100    12  20.0  2017-01-30    B   普通    否  24  男   \n",
      "328526   32817361   7354    12  20.0  2017-01-30    C   普通    否  25  男   \n",
      "328530   32817701   1041    12  20.0  2017-01-30    C   普通    否  24  男   \n",
      "328533   32817951   2000    12  20.0  2017-01-30    C   普通    否  26  女   \n",
      "328537   32818161   2873     6  16.0  2017-01-30    C   普通    否  28  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "2         ...      未成功认证  未成功认证  未成功认证  未成功认证        5  21894.0  11726.32   \n",
      "5         ...       成功认证  未成功认证  未成功认证  未成功认证        7  35622.0      0.00   \n",
      "7         ...       成功认证  未成功认证  未成功认证  未成功认证        7  35000.0   4078.61   \n",
      "10        ...       成功认证  未成功认证  未成功认证  未成功认证       12  71701.0   8109.78   \n",
      "11        ...       成功认证  未成功认证  未成功认证  未成功认证       12  79566.0      0.00   \n",
      "13        ...       成功认证  未成功认证   成功认证  未成功认证       12  54122.0   8388.58   \n",
      "16        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "18        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   3827.98   \n",
      "19        ...      未成功认证  未成功认证  未成功认证  未成功认证        7  31100.0   7942.98   \n",
      "20        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10128.0   3284.98   \n",
      "21        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "22        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1043.36   \n",
      "23        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  12700.0   1703.56   \n",
      "24        ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "26        ...      未成功认证   成功认证  未成功认证  未成功认证        3   9500.0   5452.42   \n",
      "27        ...       成功认证  未成功认证  未成功认证  未成功认证        3   9399.0   3130.15   \n",
      "28        ...       成功认证   成功认证  未成功认证  未成功认证        5  22100.0   6015.72   \n",
      "29        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  12000.0   6766.82   \n",
      "30        ...      未成功认证   成功认证  未成功认证  未成功认证        6  23000.0   7633.48   \n",
      "31        ...       成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   1651.70   \n",
      "33        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10000.0   4393.83   \n",
      "35        ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "36        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10500.0   6078.40   \n",
      "37        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "38        ...       成功认证   成功认证  未成功认证  未成功认证        3  11900.0      0.00   \n",
      "39        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  12788.0   7685.42   \n",
      "40        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  13500.0   8607.48   \n",
      "41        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  12200.0   4796.70   \n",
      "42        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0    786.71   \n",
      "44        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "328385    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0   3658.50   \n",
      "328393    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2100.0   1598.27   \n",
      "328394    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6940.0   4946.45   \n",
      "328395    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   3100.0   2580.66   \n",
      "328399    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1018.31   \n",
      "328408    ...      未成功认证   成功认证  未成功认证  未成功认证        9  23423.0  12948.79   \n",
      "328416    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1018.31   \n",
      "328421    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1600.0   1217.74   \n",
      "328423    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   7300.0   3000.00   \n",
      "328426    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7000.0   3182.80   \n",
      "328427    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5848.0   4584.22   \n",
      "328429    ...       成功认证   成功认证  未成功认证  未成功认证       12  64358.0  33767.04   \n",
      "328432    ...      未成功认证   成功认证  未成功认证  未成功认证        1   5500.0   1866.87   \n",
      "328445    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1500.0      0.00   \n",
      "328454    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1800.0   1369.96   \n",
      "328463    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5000.0   2320.48   \n",
      "328466    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5500.0   3798.18   \n",
      "328467    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   5500.0   2935.20   \n",
      "328475    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2000.0    910.63   \n",
      "328477    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6136.0   4518.14   \n",
      "328484    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5000.0   1697.17   \n",
      "328495    ...      未成功认证   成功认证  未成功认证  未成功认证        4   8969.0   5599.62   \n",
      "328500    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   8823.0   6303.85   \n",
      "328505    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5000.0    384.47   \n",
      "328516    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  22360.0  11877.89   \n",
      "328524    ...      未成功认证   成功认证  未成功认证  未成功认证        2   6164.0   4301.54   \n",
      "328526    ...      未成功认证   成功认证  未成功认证  未成功认证        6  30639.0  10175.77   \n",
      "328530    ...       成功认证  未成功认证  未成功认证  未成功认证        4   4415.0   3058.81   \n",
      "328533    ...      未成功认证   成功认证  未成功认证  未成功认证        3  12475.0   7223.48   \n",
      "328537    ...       成功认证   成功认证   成功认证  未成功认证        9  33377.0  18207.50   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "2             25         3  10.714286  \n",
      "5             56         0   0.000000  \n",
      "7             52         0   0.000000  \n",
      "10            82         0   0.000000  \n",
      "11            82         0   0.000000  \n",
      "13            34         0   0.000000  \n",
      "16             2         0   0.000000  \n",
      "18             4         2  33.333333  \n",
      "19            12         9  42.857143  \n",
      "20            17         9  34.615385  \n",
      "21             1         0   0.000000  \n",
      "22             8         0   0.000000  \n",
      "23            19         0   0.000000  \n",
      "24             6         1  14.285714  \n",
      "26             5         2  28.571429  \n",
      "27            10         0   0.000000  \n",
      "28            19         0   0.000000  \n",
      "29            13         1   7.142857  \n",
      "30            34         4  10.526316  \n",
      "31             8         5  38.461538  \n",
      "33            12         0   0.000000  \n",
      "35             4         0   0.000000  \n",
      "36            13         0   0.000000  \n",
      "37             2         0   0.000000  \n",
      "38            12         0   0.000000  \n",
      "39            17         0   0.000000  \n",
      "40            13         0   0.000000  \n",
      "41            10         0   0.000000  \n",
      "42             9         0   0.000000  \n",
      "44             6         1  14.285714  \n",
      "...          ...       ...        ...  \n",
      "328385         8         0   0.000000  \n",
      "328393         3         0   0.000000  \n",
      "328394         6         0   0.000000  \n",
      "328395         5         0   0.000000  \n",
      "328399         4         0   0.000000  \n",
      "328408        45         4   8.163265  \n",
      "328416         4         0   0.000000  \n",
      "328421         3         0   0.000000  \n",
      "328423        22         2   8.333333  \n",
      "328426         7         0   0.000000  \n",
      "328427         7         0   0.000000  \n",
      "328429        47         1   2.083333  \n",
      "328432         4         0   0.000000  \n",
      "328445         5         1  16.666667  \n",
      "328454         3         0   0.000000  \n",
      "328463         6         1  14.285714  \n",
      "328466         4         0   0.000000  \n",
      "328467        19         0   0.000000  \n",
      "328475         6         1  14.285714  \n",
      "328477         7         0   0.000000  \n",
      "328484         4         0   0.000000  \n",
      "328495        16         0   0.000000  \n",
      "328500        10         0   0.000000  \n",
      "328505        11         2  15.384615  \n",
      "328516        24         0   0.000000  \n",
      "328524         5         3  37.500000  \n",
      "328526        33         5  13.157895  \n",
      "328530        16         0   0.000000  \n",
      "328533         8         1  11.111111  \n",
      "328537        26         1   3.703704  \n",
      "\n",
      "[67969 rows x 22 columns],         ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别  \\\n",
      "0          126541  18000    12  18.0  2015-05-04    C   其他    否  35  男   \n",
      "1          133291   9453    12  20.0  2015-03-16    D   其他    否  34  男   \n",
      "3          149711  25000    12  18.0  2015-03-30    C   其他    否  34  男   \n",
      "8          182261  25000    12  16.0  2015-03-21    B   其他    否  33  女   \n",
      "12         209381  30000    24  16.0  2015-06-28    E   其他    否  30  男   \n",
      "14         528911  11000    12  20.0  2015-03-10    C   其他    否  47  男   \n",
      "25        1541641  11578    12  20.0  2015-01-04    D   其他    否  27  男   \n",
      "32        1548231   8000    12  20.0  2015-01-04    D   其他    否  27  男   \n",
      "48        1557241   9243    12  18.0  2015-01-07    C   其他    否  28  女   \n",
      "52        1559191  12383    12  20.0  2015-01-07    C   其他    否  32  男   \n",
      "53        1559261  10000    12  18.0  2015-01-07    C   其他    否  36  男   \n",
      "60        1568981  15000    12  20.0  2015-01-07    C   其他    否  33  男   \n",
      "70        1573441  12831    12  22.0  2015-01-07    D   其他    否  27  男   \n",
      "73        1574701  10000    12  20.0  2015-01-07    C   其他    否  26  男   \n",
      "75        1578391   7200    12  18.0  2015-01-07    C   其他    否  34  男   \n",
      "84        1580631  25000    12  20.0  2015-01-01    C   其他    否  32  男   \n",
      "96        1585561  10000    12  20.0  2015-01-07    D   其他    否  45  男   \n",
      "99        1586381  10000    12  20.0  2015-01-04    C   其他    否  21  男   \n",
      "142       1607591  10000    12  18.0  2015-01-13    C   其他    否  30  男   \n",
      "144       1607771  10000    12  20.0  2015-01-14    E   其他    否  29  男   \n",
      "165       1616241   1000     1  18.0  2015-01-06    D   其他    否  38  男   \n",
      "176       1623301   9734    12  20.0  2015-01-06    E   其他    否  23  男   \n",
      "177       1623481  10000    12  20.0  2015-01-13    C   其他    否  36  男   \n",
      "184       1628561  16000    12  20.0  2015-01-14    C   其他    否  27  男   \n",
      "186       1628811  10000    12  22.0  2015-01-13    D   其他    否  27  女   \n",
      "192       1630591  12058     6  18.0  2015-01-09    C   其他    否  43  男   \n",
      "194       1631401  50000     6  18.0  2015-01-21    D   其他    否  43  男   \n",
      "206       1635701   6828    12  18.0  2015-01-22    C   其他    否  24  男   \n",
      "207       1636021  12510    12  18.0  2015-01-22    C   其他    否  39  男   \n",
      "208       1636071  10773    12  20.0  2015-01-15    D   其他    否  41  女   \n",
      "...           ...    ...   ...   ...         ...  ...  ...  ...  .. ..   \n",
      "328483   32813161   2238     6  20.0  2017-01-30    C   其他    否  38  男   \n",
      "328486   32813431   2026     6  20.0  2017-01-30    C   其他    否  29  女   \n",
      "328491   32814011   2320     6  16.0  2017-01-30    A   其他    否  31  女   \n",
      "328493   32814121   2500     6  20.0  2017-01-30    C   其他    否  36  男   \n",
      "328497   32814351   5000     6  20.0  2017-01-30    C   其他    否  39  女   \n",
      "328498   32814491   3000    12  20.0  2017-01-30    C   其他    否  25  男   \n",
      "328499   32814611   2119     6  20.0  2017-01-30    D   其他    否  40  女   \n",
      "328502   32814971   2354    12  16.0  2017-01-30    C   其他    否  23  女   \n",
      "328506   32815221   4782    12  20.0  2017-01-30    C   其他    否  23  男   \n",
      "328507   32815401   4497    12  22.0  2017-01-30    C   其他    否  38  女   \n",
      "328508   32815411   2000    10  20.0  2017-01-30    C   其他    否  26  男   \n",
      "328518   32816561   2431    12  22.0  2017-01-30    D   其他    否  43  男   \n",
      "328519   32816991   2000     6  20.0  2017-01-30    D   其他    否  35  男   \n",
      "328520   32817051   2351     6  20.0  2017-01-30    C   其他    否  53  女   \n",
      "328523   32817151   4564     6  20.0  2017-01-30    C   其他    否  30  男   \n",
      "328525   32817231   2365    12  18.0  2017-01-30    B   其他    否  28  女   \n",
      "328528   32817451   2000     6  18.0  2017-01-30    C   其他    否  27  女   \n",
      "328529   32817621   5000    12  18.0  2017-01-30    B   其他    否  24  女   \n",
      "328532   32817821   2807    12  22.0  2017-01-30    D   其他    否  38  女   \n",
      "328539   32818231   2256     6  20.0  2017-01-30    C   其他    否  39  男   \n",
      "328542   32818621   3500     6  20.0  2017-01-30    C   其他    否  34  男   \n",
      "328543   32818851   5804    12  20.0  2017-01-30    C   其他    否  44  男   \n",
      "328544   32818871   6880     6  20.0  2017-01-30    C   其他    否  28  男   \n",
      "328545   32818901   5008    12  20.0  2017-01-30    C   其他    否  28  男   \n",
      "328547   32818941   2200    12  22.0  2017-01-30    D   其他    否  32  男   \n",
      "328548   32819271   2389     6  20.0  2017-01-30    C   其他    否  26  男   \n",
      "328549   32819381   7000    12  20.0  2017-01-30    C   其他    否  22  男   \n",
      "328550   32819451   2017     6  20.0  2017-01-30    C   其他    否  36  女   \n",
      "328551   32819511   6406    12  20.0  2017-01-30    C   其他    否  33  男   \n",
      "328552   32819531   3440    12  22.0  2017-01-30    D   其他    否  27  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  \\\n",
      "0         ...       成功认证  未成功认证  未成功认证  未成功认证       11   40326.0   8712.73   \n",
      "1         ...      未成功认证  未成功认证  未成功认证  未成功认证        4   14500.0   7890.64   \n",
      "3         ...       成功认证  未成功认证  未成功认证  未成功认证        6   36190.0   9703.41   \n",
      "8         ...       成功认证  未成功认证  未成功认证  未成功认证        7   42530.0   7418.35   \n",
      "12        ...       成功认证  未成功认证  未成功认证  未成功认证        7   39000.0      0.00   \n",
      "14        ...      未成功认证  未成功认证  未成功认证  未成功认证        5   17809.0   3589.14   \n",
      "25        ...       成功认证  未成功认证  未成功认证  未成功认证        4   20366.0   8378.53   \n",
      "32        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "48        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10000.0   4430.56   \n",
      "52        ...      未成功认证   成功认证  未成功认证  未成功认证        4   15232.0   4598.51   \n",
      "53        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   15051.0   5177.22   \n",
      "60        ...      未成功认证   成功认证  未成功认证  未成功认证        6   24357.0   3951.51   \n",
      "70        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   13518.0   7250.91   \n",
      "73        ...      未成功认证   成功认证  未成功认证  未成功认证        2    8000.0   5244.08   \n",
      "75        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   17047.0   6213.00   \n",
      "84        ...      未成功认证   成功认证  未成功认证  未成功认证        7   33800.0   7976.74   \n",
      "96        ...      未成功认证  未成功认证  未成功认证  未成功认证        2    7000.0   3349.81   \n",
      "99        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   1073.48   \n",
      "142       ...       成功认证  未成功认证  未成功认证  未成功认证        5   15500.0   4615.95   \n",
      "144       ...      未成功认证  未成功认证  未成功认证  未成功认证        3   11012.0   5479.35   \n",
      "165       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1000.0      0.00   \n",
      "176       ...      未成功认证  未成功认证  未成功认证  未成功认证        2    9734.0   5173.56   \n",
      "177       ...      未成功认证   成功认证  未成功认证  未成功认证        3   11800.0   5970.55   \n",
      "184       ...       成功认证  未成功认证  未成功认证  未成功认证        8   33100.0   2750.82   \n",
      "186       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   1043.36   \n",
      "192       ...      未成功认证   成功认证  未成功认证  未成功认证        4   17625.0   7785.57   \n",
      "194       ...       成功认证  未成功认证  未成功认证  未成功认证        2  110000.0  10375.86   \n",
      "206       ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6000.0   2524.55   \n",
      "207       ...       成功认证   成功认证  未成功认证  未成功认证        6   22034.0   6571.20   \n",
      "208       ...      未成功认证  未成功认证  未成功认证  未成功认证        5   16120.0   8904.56   \n",
      "...       ...        ...    ...    ...    ...      ...       ...       ...   \n",
      "328483    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    8274.0   5261.35   \n",
      "328486    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   10500.0   7973.21   \n",
      "328491    ...      未成功认证   成功认证  未成功认证  未成功认证        9   34520.0  18642.04   \n",
      "328493    ...       成功认证   成功认证  未成功认证  未成功认证        7   32240.0  21324.96   \n",
      "328497    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2000.0   1359.71   \n",
      "328498    ...      未成功认证   成功认证  未成功认证  未成功认证        4   16500.0  11211.00   \n",
      "328499    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   13500.0   7360.06   \n",
      "328502    ...      未成功认证   成功认证  未成功认证  未成功认证        4   18836.0  10595.93   \n",
      "328506    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1600.0   1217.74   \n",
      "328507    ...      未成功认证   成功认证  未成功认证  未成功认证        1    4200.0   1502.89   \n",
      "328508    ...      未成功认证   成功认证  未成功认证  未成功认证        2    5000.0   4359.71   \n",
      "328518    ...      未成功认证  未成功认证  未成功认证  未成功认证        5   19842.0   8068.86   \n",
      "328519    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    8000.0   4982.88   \n",
      "328520    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    4699.0   1148.68   \n",
      "328523    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3200.0   2435.46   \n",
      "328525    ...       成功认证  未成功认证  未成功认证  未成功认证        5   20256.0  11434.94   \n",
      "328528    ...      未成功认证  未成功认证  未成功认证  未成功认证       10   32000.0  23591.95   \n",
      "328529    ...      未成功认证   成功认证   成功认证  未成功认证       11   39730.0  18516.42   \n",
      "328532    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    5140.0   3692.90   \n",
      "328539    ...      未成功认证   成功认证  未成功认证  未成功认证        6   27142.0  15743.41   \n",
      "328542    ...      未成功认证   成功认证  未成功认证  未成功认证        7   26502.0   6916.73   \n",
      "328543    ...      未成功认证   成功认证  未成功认证  未成功认证        3   12421.0   5395.26   \n",
      "328544    ...      未成功认证   成功认证  未成功认证  未成功认证        5   19208.0  16184.84   \n",
      "328545    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   10500.0   7727.37   \n",
      "328547    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    7200.0   1154.51   \n",
      "328548    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   10000.0   7610.82   \n",
      "328549    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2100.0      0.00   \n",
      "328550    ...       成功认证  未成功认证  未成功认证  未成功认证        5   19656.0  10982.53   \n",
      "328551    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3500.0   1593.59   \n",
      "328552    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    4500.0   3059.31   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "0             57        16  21.917808  \n",
      "1             13         1   7.142857  \n",
      "3             41         1   2.380952  \n",
      "8             41         2   4.651163  \n",
      "12            27         1   3.571429  \n",
      "14            25         2   7.407407  \n",
      "25             9         0   0.000000  \n",
      "32             7         0   0.000000  \n",
      "48            13         0   0.000000  \n",
      "52            18         0   0.000000  \n",
      "53            14         0   0.000000  \n",
      "60            24         3  11.111111  \n",
      "70            18         0   0.000000  \n",
      "73             9         0   0.000000  \n",
      "75             8         0   0.000000  \n",
      "84            21         1   4.545455  \n",
      "96             8         0   0.000000  \n",
      "99             8         0   0.000000  \n",
      "142           16         0   0.000000  \n",
      "144           12         0   0.000000  \n",
      "165            1         0   0.000000  \n",
      "176           10         0   0.000000  \n",
      "177           13         0   0.000000  \n",
      "184           59         4   6.349206  \n",
      "186            8         0   0.000000  \n",
      "192           15         2  11.764706  \n",
      "194            8         3  27.272727  \n",
      "206            9         0   0.000000  \n",
      "207           24         1   4.000000  \n",
      "208           21         1   4.545455  \n",
      "...          ...       ...        ...  \n",
      "328483        10         0   0.000000  \n",
      "328486         6         0   0.000000  \n",
      "328491        26         0   0.000000  \n",
      "328493         9         2  18.181818  \n",
      "328497         4         0   0.000000  \n",
      "328498        15         0   0.000000  \n",
      "328499        11         0   0.000000  \n",
      "328502        24         0   0.000000  \n",
      "328506         2         1  33.333333  \n",
      "328507         6         2  25.000000  \n",
      "328508         4         0   0.000000  \n",
      "328518        21        10  32.258065  \n",
      "328519        13         0   0.000000  \n",
      "328520        10         3  23.076923  \n",
      "328523         3         0   0.000000  \n",
      "328525        22         0   0.000000  \n",
      "328528        17         0   0.000000  \n",
      "328529        66         0   0.000000  \n",
      "328532         8         0   0.000000  \n",
      "328539        24         0   0.000000  \n",
      "328542        45         0   0.000000  \n",
      "328543        15         1   6.250000  \n",
      "328544         9         2  18.181818  \n",
      "328545        14         0   0.000000  \n",
      "328547        15         3  16.666667  \n",
      "328548         3         0   0.000000  \n",
      "328549        12         0   0.000000  \n",
      "328550        20         2   9.090909  \n",
      "328551         7         0   0.000000  \n",
      "328552         4         0   0.000000  \n",
      "\n",
      "[90242 rows x 22 columns]]\n"
     ]
    }
   ],
   "source": [
    "kind_idx=('电商','APP闪电','普通','其他')\n",
    "kind=[]\n",
    "for i in kind_idx:\n",
    "    temp = LC[LC['借款类型'] == i]\n",
    "    kind.append(temp)\n",
    "print(kind)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 不同借款金额的数据划分 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:38:07.306107Z",
     "start_time": "2020-07-30T13:38:06.918219Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(        ListingId  借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "89        1582411  1000     7  23.0  2015-01-06    D     普通    否  22  男   \n",
      "102       1586811  1000     7  23.0  2015-01-04    D     普通    否  21  男   \n",
      "109       1591511  1000     7  23.0  2015-01-04    C     普通    否  22  男   \n",
      "165       1616241  1000     1  18.0  2015-01-06    D     其他    否  38  男   \n",
      "216       1639111  1000     7  23.0  2015-01-09    E     普通    否  21  男   \n",
      "238       1649491  1000     1  18.0  2015-01-12    D     其他    否  33  男   \n",
      "304       1673981  1000     1  18.0  2015-01-14    D     其他    否  32  男   \n",
      "325       1679951  1000     7  23.0  2015-01-15    E     普通    否  22  男   \n",
      "330       1681911  1000     7  23.0  2015-01-15    C     普通    否  21  女   \n",
      "332       1682501  1000     1  18.0  2015-01-15    D     其他    否  33  男   \n",
      "351       1687411  1000     7  23.0  2015-01-16    D     普通    否  21  男   \n",
      "388       1696561  1000     7  23.0  2015-01-19    C     普通    否  24  男   \n",
      "418       1707281  1000     7  23.0  2015-01-20    E     普通    否  24  男   \n",
      "429       1710591  1000     1  18.0  2015-01-20    D     其他    否  31  女   \n",
      "437       1712471  1000     7  23.0  2015-01-21    D     普通    否  23  男   \n",
      "451       1716081  1000     7  23.0  2015-01-22    C     普通    否  23  男   \n",
      "456       1717331  1000     1  18.0  2015-01-21    D     其他    否  27  女   \n",
      "519       1734791  1000     1  18.0  2015-01-27    D     其他    否  31  男   \n",
      "529       1738091  1000     7  23.0  2015-01-26    D     普通    否  22  男   \n",
      "544       1742501  1000     7  23.0  2015-01-27    C     普通    否  23  男   \n",
      "557       1746591  1000     1  18.0  2015-01-27    D     其他    否  26  女   \n",
      "568       1748501  1000     1  18.0  2015-01-28    D     其他    否  41  男   \n",
      "584       1752011  1000     1  18.0  2015-01-28    D     其他    否  31  男   \n",
      "587       1753531  1000     7  23.0  2015-02-03    D     普通    否  23  男   \n",
      "592       1754371  1000     1  18.0  2015-01-29    D     其他    否  30  男   \n",
      "608       1759061  1000     1  18.0  2015-01-30    D     其他    否  31  男   \n",
      "611       1759981  1000     1  18.0  2015-01-30    D     其他    否  32  男   \n",
      "667       1783001  1000     7  23.0  2015-02-03    C     普通    否  24  男   \n",
      "677       1785021  1000     1  18.0  2015-02-04    D     其他    否  29  男   \n",
      "681       1785381  1000     1  18.0  2015-02-04    D     其他    否  26  男   \n",
      "...           ...   ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328443   32810071  1309    12  22.0  2017-01-30    D  APP闪电    否  30  男   \n",
      "328444   32810151  1554    12  22.0  2017-01-30    D  APP闪电    否  33  男   \n",
      "328447   32810581   989    12  22.0  2017-01-30    D  APP闪电    否  32  男   \n",
      "328449   32810671   700    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328451   32810731  1100    12  22.0  2017-01-30    D  APP闪电    否  35  男   \n",
      "328452   32810811  1975    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328457   32811291  1000    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "328462   32811611  1996    12  18.0  2017-01-30    B  APP闪电    否  24  男   \n",
      "328465   32811921  1000    12  18.0  2017-01-30    B  APP闪电    否  19  女   \n",
      "328471   32812331  1179    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "328472   32812341  1000    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328474   32812631  1581    12  22.0  2017-01-30    D  APP闪电    否  29  男   \n",
      "328476   32812671  1868     6  18.0  2017-01-30    B  APP闪电    否  32  男   \n",
      "328485   32813391   700    12  20.0  2017-01-30    C  APP闪电    否  23  女   \n",
      "328492   32814071   955    12  22.0  2017-01-30    D  APP闪电    否  41  男   \n",
      "328494   32814141   995    12  18.0  2017-01-30    B  APP闪电    否  35  女   \n",
      "328496   32814211  1313    12  22.0  2017-01-30    D  APP闪电    否  27  男   \n",
      "328501   32814781  1556     6  18.0  2017-01-30    B  APP闪电    否  29  女   \n",
      "328509   32815421  1396    12  22.0  2017-01-30    D  APP闪电    否  35  男   \n",
      "328511   32815751   990    12  22.0  2017-01-30    D  APP闪电    否  36  男   \n",
      "328515   32816321   700    12  22.0  2017-01-30    D  APP闪电    否  22  女   \n",
      "328527   32817401  1200    12  20.0  2017-01-30    C  APP闪电    否  22  男   \n",
      "328530   32817701  1041    12  20.0  2017-01-30    C     普通    否  24  男   \n",
      "328531   32817811   730    12  22.0  2017-01-30    D  APP闪电    否  30  女   \n",
      "328534   32818011   728    12  20.0  2017-01-30    C  APP闪电    否  36  男   \n",
      "328535   32818041   782     6  20.0  2017-01-30    C  APP闪电    否  38  女   \n",
      "328536   32818051  1175    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328538   32818171  1677    12  22.0  2017-01-30    D  APP闪电    否  24  男   \n",
      "328540   32818411  1814    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328546   32818911   782    12  22.0  2017-01-30    D  APP闪电    否  26  男   \n",
      "\n",
      "           ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "89         ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "102        ...       成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "109        ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "165        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "216        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "238        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "304        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "325        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "330        ...       成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "332        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "351        ...       成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "388        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "418        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "429        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "437        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "451        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "456        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "519        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "529        ...       成功认证  未成功认证  未成功认证  未成功认证        3   3000.0      0.00   \n",
      "544        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "557        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0   1000.00   \n",
      "568        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   4000.0      0.00   \n",
      "584        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "587        ...       成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "592        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "608        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "611        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "667        ...       成功认证   成功认证  未成功认证  未成功认证        3   9000.0   4112.17   \n",
      "677        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2000.0      0.00   \n",
      "681        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0      0.00   \n",
      "...        ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "328443     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4000.0   2690.93   \n",
      "328444     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7152.0   3945.34   \n",
      "328447     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   2403.0    810.99   \n",
      "328449     ...      未成功认证  未成功认证  未成功认证  未成功认证        7   5900.0   5303.20   \n",
      "328451     ...      未成功认证  未成功认证  未成功认证  未成功认证        3   4565.0   2412.57   \n",
      "328452     ...      未成功认证  未成功认证  未成功认证  未成功认证        3   2300.0   1624.74   \n",
      "328457     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5817.0   2077.07   \n",
      "328462     ...      未成功认证   成功认证  未成功认证  未成功认证        7  24433.0  15003.82   \n",
      "328465     ...      未成功认证  未成功认证  未成功认证  未成功认证        3   3700.0   2975.74   \n",
      "328471     ...      未成功认证  未成功认证  未成功认证  未成功认证        3   7728.0   4320.62   \n",
      "328472     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1200.0      0.00   \n",
      "328474     ...      未成功认证  未成功认证  未成功认证  未成功认证        8  16526.0   8218.49   \n",
      "328476     ...      未成功认证   成功认证  未成功认证  未成功认证        2  11000.0   6131.95   \n",
      "328485     ...      未成功认证   成功认证  未成功认证  未成功认证        6   6953.0   5282.08   \n",
      "328492     ...      未成功认证   成功认证  未成功认证  未成功认证        1   4000.0   3044.33   \n",
      "328494     ...      未成功认证   成功认证  未成功认证  未成功认证       10  14882.0   6704.93   \n",
      "328496     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5500.0   3786.48   \n",
      "328501     ...      未成功认证   成功认证  未成功认证  未成功认证        5  16812.0   9743.68   \n",
      "328509     ...      未成功认证  未成功认证  未成功认证  未成功认证       11  16254.0   6303.57   \n",
      "328511     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1500.0    509.15   \n",
      "328515     ...      未成功认证  未成功认证  未成功认证  未成功认证        4   2250.0    749.35   \n",
      "328527     ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1750.0    603.74   \n",
      "328530     ...       成功认证  未成功认证  未成功认证  未成功认证        4   4415.0   3058.81   \n",
      "328531     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5426.0   2969.05   \n",
      "328534     ...      未成功认证   成功认证  未成功认证  未成功认证        7  10948.0   6271.30   \n",
      "328535     ...      未成功认证  未成功认证  未成功认证  未成功认证        4  14691.0  10087.86   \n",
      "328536     ...       成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3424.88   \n",
      "328538     ...      未成功认证  未成功认证  未成功认证  未成功认证        3   4805.0   2422.66   \n",
      "328540     ...      未成功认证   成功认证  未成功认证  未成功认证        2   5000.0   2885.30   \n",
      "328546     ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4818.0   3217.74   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数       逾期还款率  \n",
      "89             7         0    0.000000  \n",
      "102            4         0    0.000000  \n",
      "109           12         0    0.000000  \n",
      "165            1         0    0.000000  \n",
      "216            3         0    0.000000  \n",
      "238            0         1  100.000000  \n",
      "304            2         0    0.000000  \n",
      "325            2         0    0.000000  \n",
      "330           12         0    0.000000  \n",
      "332            1         1   50.000000  \n",
      "351            5         1   16.666667  \n",
      "388            2         0    0.000000  \n",
      "418            3         1   25.000000  \n",
      "429            0         1  100.000000  \n",
      "437            3         0    0.000000  \n",
      "451            7         0    0.000000  \n",
      "456            1         1   50.000000  \n",
      "519            2         0    0.000000  \n",
      "529            9         1   10.000000  \n",
      "544            6         0    0.000000  \n",
      "557            1         0    0.000000  \n",
      "568            4         0    0.000000  \n",
      "584            1         1   50.000000  \n",
      "587            5         1   16.666667  \n",
      "592            1         1   50.000000  \n",
      "608            1         1   50.000000  \n",
      "611            1         1   50.000000  \n",
      "667           19         0    0.000000  \n",
      "677            1         1   50.000000  \n",
      "681            0         1  100.000000  \n",
      "...          ...       ...         ...  \n",
      "328443         2         0    0.000000  \n",
      "328444         8         0    0.000000  \n",
      "328447        15         0    0.000000  \n",
      "328449        11         0    0.000000  \n",
      "328451         6         0    0.000000  \n",
      "328452         7         0    0.000000  \n",
      "328457        10         0    0.000000  \n",
      "328462        47         0    0.000000  \n",
      "328465         7         0    0.000000  \n",
      "328471         7         0    0.000000  \n",
      "328472         6         0    0.000000  \n",
      "328474        27         0    0.000000  \n",
      "328476         9         0    0.000000  \n",
      "328485        17         0    0.000000  \n",
      "328492         3         0    0.000000  \n",
      "328494        52         0    0.000000  \n",
      "328496         4         0    0.000000  \n",
      "328501        20         0    0.000000  \n",
      "328509        52         0    0.000000  \n",
      "328511         3         1   25.000000  \n",
      "328515        24         2    7.692308  \n",
      "328527         8         0    0.000000  \n",
      "328530        16         0    0.000000  \n",
      "328531         5         0    0.000000  \n",
      "328534        28         0    0.000000  \n",
      "328535         7         0    0.000000  \n",
      "328536         3         0    0.000000  \n",
      "328538        10         0    0.000000  \n",
      "328540         7         0    0.000000  \n",
      "328546         4         1   20.000000  \n",
      "\n",
      "[58916 rows x 22 columns],         ListingId  借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "1463      1981191  2600     3  22.0  2015-03-16    D     其他    否  30  男   \n",
      "2057      2129821  2000     3  22.0  2015-04-09    D     其他    否  26  男   \n",
      "2247      2174471  2000     3  22.0  2015-04-14    D     其他    否  28  女   \n",
      "3798      2703411  2000     6  22.0  2015-06-16    D     其他    否  29  男   \n",
      "4444      2883961  2100     6  18.0  2015-06-26    C     其他    否  29  男   \n",
      "4499      2891311  2000     6  18.0  2015-06-24    C     其他    否  26  男   \n",
      "4522      2899481  2600     6  18.0  2015-06-26    C     其他    否  24  女   \n",
      "4530      2902371  2000     3  24.0  2015-07-04    D     其他    否  28  男   \n",
      "4582      2919051  2100    12  20.0  2015-06-24    D     其他    否  34  男   \n",
      "4601      2923621  2000    12  20.0  2015-07-01    D     其他    否  26  男   \n",
      "4779      2958471  2445     6  18.0  2015-06-26    C     其他    否  35  男   \n",
      "4889      2994331  2150     6  18.0  2015-07-01    C     其他    否  26  男   \n",
      "4964      3009961  2000     6  18.0  2015-07-06    C     其他    否  22  男   \n",
      "4996      3015021  2000     6  18.0  2015-07-01    C     其他    否  29  男   \n",
      "5002      3016121  2900     6  18.0  2015-07-01    D     其他    否  29  男   \n",
      "5254      3060221  2660    12  20.0  2015-07-10    D     其他    否  23  男   \n",
      "5283      3068491  2210    12  20.0  2015-07-11    D     其他    否  29  男   \n",
      "5312      3073461  2500     6  18.0  2015-07-07    C     普通    否  24  男   \n",
      "5363      3089581  2000    12  20.0  2015-07-13    D     其他    否  33  男   \n",
      "5453      3114291  2463    12  20.0  2015-07-11    D     其他    否  27  男   \n",
      "5543      3130891  2200     6  18.0  2015-07-09    C     其他    否  33  男   \n",
      "5558      3133601  2800     6  18.0  2015-07-10    C     其他    否  30  男   \n",
      "5576      3139391  2000     6  18.0  2015-07-09    C     其他    否  34  男   \n",
      "5649      3156181  2700     6  18.0  2015-07-10    C     其他    否  41  女   \n",
      "5764      3182241  2000     8  18.0  2015-07-13    C     其他    否  23  男   \n",
      "5826      3196121  2600    12  20.0  2015-07-23    D     其他    否  24  女   \n",
      "6079      3255711  2000     6  20.0  2015-07-20    C     其他    否  26  男   \n",
      "6085      3256241  2300     6  18.0  2015-07-20    B     其他    否  23  男   \n",
      "6168      3286561  2375     6  20.0  2015-07-20    C     其他    否  27  男   \n",
      "6221      3300451  2520     6  20.0  2015-07-22    C     其他    否  28  男   \n",
      "...           ...   ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328477   32812681  2482    12  22.0  2017-01-30    D     普通    否  28  男   \n",
      "328478   32812801  2000    12  22.0  2017-01-30    C     其他    否  21  男   \n",
      "328480   32813011  2000    12  22.0  2017-01-30    D     其他    否  25  男   \n",
      "328481   32813051  2400    12  22.0  2017-01-30    C     其他    否  27  男   \n",
      "328482   32813081  2768     6  20.0  2017-01-30    C     其他    否  31  男   \n",
      "328483   32813161  2238     6  20.0  2017-01-30    C     其他    否  38  男   \n",
      "328486   32813431  2026     6  20.0  2017-01-30    C     其他    否  29  女   \n",
      "328489   32813661  2800    12  22.0  2017-01-30    D  APP闪电    否  32  男   \n",
      "328490   32813831  2885    12  18.0  2017-01-30    B  APP闪电    否  30  男   \n",
      "328491   32814011  2320     6  16.0  2017-01-30    A     其他    否  31  女   \n",
      "328493   32814121  2500     6  20.0  2017-01-30    C     其他    否  36  男   \n",
      "328499   32814611  2119     6  20.0  2017-01-30    D     其他    否  40  女   \n",
      "328500   32814731  2696    12  20.0  2017-01-30    C     普通    否  41  男   \n",
      "328502   32814971  2354    12  16.0  2017-01-30    C     其他    否  23  女   \n",
      "328508   32815411  2000    10  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328510   32815471  2571    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328517   32816441  2500    12  20.0  2017-01-30    C  APP闪电    否  23  男   \n",
      "328518   32816561  2431    12  22.0  2017-01-30    D     其他    否  43  男   \n",
      "328519   32816991  2000     6  20.0  2017-01-30    D     其他    否  35  男   \n",
      "328520   32817051  2351     6  20.0  2017-01-30    C     其他    否  53  女   \n",
      "328525   32817231  2365    12  18.0  2017-01-30    B     其他    否  28  女   \n",
      "328528   32817451  2000     6  18.0  2017-01-30    C     其他    否  27  女   \n",
      "328532   32817821  2807    12  22.0  2017-01-30    D     其他    否  38  女   \n",
      "328533   32817951  2000    12  20.0  2017-01-30    C     普通    否  26  女   \n",
      "328537   32818161  2873     6  16.0  2017-01-30    C     普通    否  28  男   \n",
      "328539   32818231  2256     6  20.0  2017-01-30    C     其他    否  39  男   \n",
      "328541   32818591  2067    12  22.0  2017-01-30    D  APP闪电    否  23  男   \n",
      "328547   32818941  2200    12  22.0  2017-01-30    D     其他    否  32  男   \n",
      "328548   32819271  2389     6  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328550   32819451  2017     6  20.0  2017-01-30    C     其他    否  36  女   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "1463      ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0    522.99   \n",
      "2057      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2000.0      0.00   \n",
      "2247      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2000.0      0.00   \n",
      "3798      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2000.0      0.00   \n",
      "4444      ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0   2283.25   \n",
      "4499      ...      未成功认证  未成功认证  未成功认证  未成功认证        8  28200.0   8362.96   \n",
      "4522      ...      未成功认证   成功认证  未成功认证  未成功认证        2   6702.0   2504.56   \n",
      "4530      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2000.0      0.00   \n",
      "4582      ...      未成功认证  未成功认证  未成功认证  未成功认证        4  15700.0   8039.55   \n",
      "4601      ...       成功认证   成功认证  未成功认证  未成功认证        1   3000.0   1739.84   \n",
      "4779      ...      未成功认证   成功认证  未成功认证  未成功认证        1   4500.0   3029.76   \n",
      "4889      ...      未成功认证   成功认证  未成功认证  未成功认证        1   1000.0    849.40   \n",
      "4964      ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "4996      ...       成功认证   成功认证  未成功认证  未成功认证        3  10150.0   5441.73   \n",
      "5002      ...      未成功认证  未成功认证  未成功认证  未成功认证        7  30390.0  15041.53   \n",
      "5254      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0    170.49   \n",
      "5283      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0    783.93   \n",
      "5312      ...       成功认证  未成功认证  未成功认证  未成功认证        3   5000.0   1377.67   \n",
      "5363      ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0   2164.08   \n",
      "5453      ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9476.0   3831.71   \n",
      "5543      ...       成功认证  未成功认证   成功认证  未成功认证        7  35814.0  12474.37   \n",
      "5558      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5500.0   2824.93   \n",
      "5576      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4000.0   2690.93   \n",
      "5649      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5500.0   3967.47   \n",
      "5764      ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0   2283.25   \n",
      "5826      ...      未成功认证  未成功认证   成功认证  未成功认证        1   3000.0   1311.35   \n",
      "6079      ...      未成功认证   成功认证   成功认证  未成功认证        1   3000.0   2018.20   \n",
      "6085      ...      未成功认证   成功认证  未成功认证  未成功认证        1   1000.0    672.73   \n",
      "6168      ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   2018.20   \n",
      "6221      ...      未成功认证   成功认证   成功认证  未成功认证        3  10600.0   5471.14   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "328477    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6136.0   4518.14   \n",
      "328478    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    500.0     87.52   \n",
      "328480    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0    679.87   \n",
      "328481    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4100.0   3100.00   \n",
      "328482    ...      未成功认证   成功认证  未成功认证  未成功认证        4  15900.0   7731.59   \n",
      "328483    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   8274.0   5261.35   \n",
      "328486    ...      未成功认证  未成功认证  未成功认证  未成功认证        2  10500.0   7973.21   \n",
      "328489    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  10667.0   3993.59   \n",
      "328490    ...      未成功认证   成功认证  未成功认证  未成功认证        6  15091.0   7514.90   \n",
      "328491    ...      未成功认证   成功认证  未成功认证  未成功认证        9  34520.0  18642.04   \n",
      "328493    ...       成功认证   成功认证  未成功认证  未成功认证        7  32240.0  21324.96   \n",
      "328499    ...      未成功认证  未成功认证  未成功认证  未成功认证        3  13500.0   7360.06   \n",
      "328500    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   8823.0   6303.85   \n",
      "328502    ...      未成功认证   成功认证  未成功认证  未成功认证        4  18836.0  10595.93   \n",
      "328508    ...      未成功认证   成功认证  未成功认证  未成功认证        2   5000.0   4359.71   \n",
      "328510    ...      未成功认证  未成功认证  未成功认证  未成功认证       10  16548.0   6328.08   \n",
      "328517    ...      未成功认证   成功认证  未成功认证  未成功认证        3   2000.0   1438.58   \n",
      "328518    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  19842.0   8068.86   \n",
      "328519    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   8000.0   4982.88   \n",
      "328520    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4699.0   1148.68   \n",
      "328525    ...       成功认证  未成功认证  未成功认证  未成功认证        5  20256.0  11434.94   \n",
      "328528    ...      未成功认证  未成功认证  未成功认证  未成功认证       10  32000.0  23591.95   \n",
      "328532    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5140.0   3692.90   \n",
      "328533    ...      未成功认证   成功认证  未成功认证  未成功认证        3  12475.0   7223.48   \n",
      "328537    ...       成功认证   成功认证   成功认证  未成功认证        9  33377.0  18207.50   \n",
      "328539    ...      未成功认证   成功认证  未成功认证  未成功认证        6  27142.0  15743.41   \n",
      "328541    ...      未成功认证   成功认证  未成功认证  未成功认证        2   3993.0   3332.43   \n",
      "328547    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7200.0   1154.51   \n",
      "328548    ...      未成功认证  未成功认证  未成功认证  未成功认证        1  10000.0   7610.82   \n",
      "328550    ...       成功认证  未成功认证  未成功认证  未成功认证        5  19656.0  10982.53   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "1463           5         0   0.000000  \n",
      "2057           1         0   0.000000  \n",
      "2247           3         0   0.000000  \n",
      "3798           2         1  33.333333  \n",
      "4444           3         0   0.000000  \n",
      "4499          62         0   0.000000  \n",
      "4522           8         0   0.000000  \n",
      "4530           1         3  75.000000  \n",
      "4582          25         0   0.000000  \n",
      "4601           3         0   0.000000  \n",
      "4779           2         0   0.000000  \n",
      "4889           2         0   0.000000  \n",
      "4964           6         3  33.333333  \n",
      "4996          13         0   0.000000  \n",
      "5002          28         0   0.000000  \n",
      "5254           5         0   0.000000  \n",
      "5283           9         0   0.000000  \n",
      "5312           9         1  10.000000  \n",
      "5363           2         0   0.000000  \n",
      "5453          12         0   0.000000  \n",
      "5543          41         0   0.000000  \n",
      "5558           3         0   0.000000  \n",
      "5576           2         0   0.000000  \n",
      "5649           2         0   0.000000  \n",
      "5764           3         0   0.000000  \n",
      "5826           4         0   0.000000  \n",
      "6079           2         0   0.000000  \n",
      "6085           2         0   0.000000  \n",
      "6168           2         0   0.000000  \n",
      "6221           8         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "328477         7         0   0.000000  \n",
      "328478        10         0   0.000000  \n",
      "328480         4         0   0.000000  \n",
      "328481        11         1   8.333333  \n",
      "328482        19         1   5.000000  \n",
      "328483        10         0   0.000000  \n",
      "328486         6         0   0.000000  \n",
      "328489        18         0   0.000000  \n",
      "328490        31         0   0.000000  \n",
      "328491        26         0   0.000000  \n",
      "328493         9         2  18.181818  \n",
      "328499        11         0   0.000000  \n",
      "328500        10         0   0.000000  \n",
      "328502        24         0   0.000000  \n",
      "328508         4         0   0.000000  \n",
      "328510        45         0   0.000000  \n",
      "328517         8         0   0.000000  \n",
      "328518        21        10  32.258065  \n",
      "328519        13         0   0.000000  \n",
      "328520        10         3  23.076923  \n",
      "328525        22         0   0.000000  \n",
      "328528        17         0   0.000000  \n",
      "328532         8         0   0.000000  \n",
      "328533         8         1  11.111111  \n",
      "328537        26         1   3.703704  \n",
      "328539        24         0   0.000000  \n",
      "328541         4         0   0.000000  \n",
      "328547        15         3  16.666667  \n",
      "328548         3         0   0.000000  \n",
      "328550        20         2   9.090909  \n",
      "\n",
      "[51381 rows x 22 columns],         ListingId  借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "6          171191  3940     6  18.0  2015-06-26    E     电商    否  27  女   \n",
      "18        1536991  3885    12  24.0  2015-01-04    F     普通    否  47  女   \n",
      "19        1537191  3228    12  24.0  2015-01-02    F     普通    否  39  男   \n",
      "22        1538211  3000    12  20.0  2015-01-04    D     普通    否  23  女   \n",
      "27        1542581  3500    12  18.0  2015-01-04    C     普通    否  28  男   \n",
      "31        1547751  3900    12  23.0  2015-01-04    E     普通    否  27  男   \n",
      "36        1550751  3500    12  20.0  2015-01-05    D     普通    否  27  男   \n",
      "37        1551201  3884    12  22.0  2015-01-05    D     普通    否  25  男   \n",
      "40        1551871  3500    12  21.0  2015-01-05    D     普通    否  23  男   \n",
      "45        1555121  3158    12  20.0  2015-01-07    D     普通    否  23  女   \n",
      "46        1557141  3500    12  24.0  2015-01-04    F     普通    否  32  男   \n",
      "51        1558971  3714    12  20.0  2015-01-06    D     普通    否  27  男   \n",
      "56        1560601  3879    12  18.0  2015-01-07    C     普通    否  48  男   \n",
      "58        1563891  3500    12  20.0  2015-01-02    C     普通    否  38  男   \n",
      "59        1565761  3974    12  22.0  2015-01-03    D     普通    否  37  男   \n",
      "61        1569321  3700    12  22.0  2015-01-09    E     普通    否  28  男   \n",
      "63        1570471  3000    12  20.0  2015-01-05    D     普通    否  24  男   \n",
      "66        1572871  3000    12  22.0  2015-01-01    D     普通    否  28  男   \n",
      "71        1573751  3200    12  22.0  2015-01-10    E     普通    否  34  男   \n",
      "72        1574051  3200    12  22.0  2015-01-08    E     普通    否  31  男   \n",
      "94        1584961  3700    12  22.0  2015-01-08    E     普通    否  32  男   \n",
      "100       1586561  3800    12  20.0  2015-01-08    D     普通    否  31  男   \n",
      "116       1595141  3600    12  22.0  2015-01-09    E     普通    否  27  男   \n",
      "121       1596281  3000     6  18.0  2015-01-05    E     普通    否  34  男   \n",
      "122       1597201  3000    12  20.0  2015-01-08    D     普通    否  25  男   \n",
      "125       1599611  3000     6  18.0  2015-01-04    C     普通    否  38  男   \n",
      "131       1603021  3200    12  22.0  2015-01-12    E     普通    否  47  男   \n",
      "133       1603911  3000    12  20.0  2015-01-05    C     普通    否  31  男   \n",
      "152       1610851  3750     6  18.0  2015-01-08    C     普通    否  27  男   \n",
      "167       1618201  3000    12  24.0  2015-01-06    F     普通    否  41  男   \n",
      "...           ...   ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328333   32804791  3415    12  22.0  2017-01-30    D     其他    否  28  男   \n",
      "328337   32804921  3962    12  22.0  2017-01-30    D     其他    否  28  男   \n",
      "328340   32805001  3417    12  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328342   32805041  3999    12  22.0  2017-01-30    D     其他    否  43  男   \n",
      "328355   32805311  3922    12  20.0  2017-01-30    C     其他    否  23  女   \n",
      "328363   32805571  3233    12  22.0  2017-01-30    C     普通    否  33  女   \n",
      "328367   32805941  3207    12  22.0  2017-01-30    D     普通    否  34  男   \n",
      "328368   32805961  3200     6  20.0  2017-01-30    C     普通    否  25  女   \n",
      "328377   32806291  3000    12  20.0  2017-01-30    C  APP闪电    否  34  女   \n",
      "328378   32806401  3076    12  22.0  2017-01-30    D     其他    否  31  女   \n",
      "328397   32807351  3000    12  22.0  2017-01-30    D  APP闪电    否  27  女   \n",
      "328409   32807821  3872    12  22.0  2017-01-30    D     其他    否  49  男   \n",
      "328421   32808481  3782    12  22.0  2017-01-30    D     普通    否  30  女   \n",
      "328424   32808911  3075     6  20.0  2017-01-30    D     其他    否  26  男   \n",
      "328425   32808941  3139    12  22.0  2017-01-30    D     其他    否  25  女   \n",
      "328430   32809291  3800    12  22.0  2017-01-30    D     其他    否  32  男   \n",
      "328435   32809711  3572     6  18.0  2017-01-30    B  APP闪电    否  26  女   \n",
      "328440   32809831  3100    12  20.0  2017-01-30    C     其他    否  35  男   \n",
      "328446   32810341  3225     6  20.0  2017-01-30    D     其他    否  30  男   \n",
      "328448   32810631  3000    10  20.0  2017-01-30    C     其他    否  30  女   \n",
      "328455   32811111  3200     6  20.0  2017-01-30    D     其他    否  46  男   \n",
      "328459   32811371  3633    11  20.0  2017-01-30    C     其他    否  22  女   \n",
      "328470   32812251  3282    12  20.0  2017-01-30    C     其他    否  23  男   \n",
      "328495   32814151  3900    12  20.0  2017-01-30    C     普通    否  22  男   \n",
      "328498   32814491  3000    12  20.0  2017-01-30    C     其他    否  25  男   \n",
      "328513   32815871  3327    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328516   32816401  3548    12  20.0  2017-01-30    D     普通    否  38  男   \n",
      "328522   32817131  3592    12  22.0  2017-01-30    D  APP闪电    否  31  女   \n",
      "328542   32818621  3500     6  20.0  2017-01-30    C     其他    否  34  男   \n",
      "328552   32819531  3440    12  22.0  2017-01-30    D     其他    否  27  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "6         ...       成功认证  未成功认证  未成功认证  未成功认证       15  63989.0   6619.37   \n",
      "18        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   3827.98   \n",
      "19        ...      未成功认证  未成功认证  未成功认证  未成功认证        7  31100.0   7942.98   \n",
      "22        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1043.36   \n",
      "27        ...       成功认证  未成功认证  未成功认证  未成功认证        3   9399.0   3130.15   \n",
      "31        ...       成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   1651.70   \n",
      "36        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10500.0   6078.40   \n",
      "37        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "40        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  13500.0   8607.48   \n",
      "45        ...       成功认证  未成功认证  未成功认证  未成功认证        2   6300.0   1454.93   \n",
      "46        ...       成功认证  未成功认证  未成功认证  未成功认证        5  16000.0   7757.39   \n",
      "51        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0    880.34   \n",
      "56        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  15265.0   6845.33   \n",
      "58        ...       成功认证   成功认证  未成功认证  未成功认证        3   9400.0   4770.64   \n",
      "59        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   2921.14   \n",
      "61        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   2283.25   \n",
      "63        ...      未成功认证   成功认证  未成功认证  未成功认证        3  10500.0   4592.65   \n",
      "66        ...      未成功认证   成功认证  未成功认证  未成功认证        6  20600.0   6445.07   \n",
      "71        ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "72        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   2283.25   \n",
      "94        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6200.0   2688.46   \n",
      "100       ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10564.0   4157.18   \n",
      "116       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "121       ...      未成功认证  未成功认证  未成功认证  未成功认证        5  22448.0      0.00   \n",
      "122       ...       成功认证  未成功认证  未成功认证  未成功认证        5  15920.0   3404.79   \n",
      "125       ...       成功认证  未成功认证  未成功认证  未成功认证        6  28000.0   6196.01   \n",
      "131       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "133       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "152       ...       成功认证   成功认证  未成功认证  未成功认证        1   3000.0   1537.20   \n",
      "167       ...       成功认证  未成功认证  未成功认证  未成功认证        3  10574.0      0.00   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "328333    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  12744.0   6084.05   \n",
      "328337    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  14672.0   6037.26   \n",
      "328340    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7000.0   5082.18   \n",
      "328342    ...      未成功认证  未成功认证  未成功认证  未成功认证        6  15168.0   8000.10   \n",
      "328355    ...      未成功认证   成功认证  未成功认证  未成功认证        3  11805.0   6077.68   \n",
      "328363    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2500.0   1267.11   \n",
      "328367    ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0   1793.39   \n",
      "328368    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1018.31   \n",
      "328377    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2000.0   1674.23   \n",
      "328378    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4300.0   2923.34   \n",
      "328397    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   4400.0   2952.74   \n",
      "328409    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   9311.0   4227.43   \n",
      "328421    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1600.0   1217.74   \n",
      "328424    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   9734.0   5424.80   \n",
      "328425    ...      未成功认证  未成功认证  未成功认证  未成功认证       27  88648.0  35119.47   \n",
      "328430    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   8074.0   5154.49   \n",
      "328435    ...      未成功认证   成功认证  未成功认证  未成功认证       10  19670.0   6127.41   \n",
      "328440    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  17675.0   8899.99   \n",
      "328446    ...      未成功认证   成功认证  未成功认证  未成功认证        4  15711.0   6774.66   \n",
      "328448    ...      未成功认证  未成功认证  未成功认证  未成功认证        6  23269.0  11777.57   \n",
      "328455    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   9643.0   4785.81   \n",
      "328459    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0   4106.89   \n",
      "328470    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   3600.0   3217.74   \n",
      "328495    ...      未成功认证   成功认证  未成功认证  未成功认证        4   8969.0   5599.62   \n",
      "328498    ...      未成功认证   成功认证  未成功认证  未成功认证        4  16500.0  11211.00   \n",
      "328513    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1000.0    672.73   \n",
      "328516    ...      未成功认证  未成功认证  未成功认证  未成功认证        5  22360.0  11877.89   \n",
      "328522    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3107.58   \n",
      "328542    ...      未成功认证   成功认证  未成功认证  未成功认证        7  26502.0   6916.73   \n",
      "328552    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4500.0   3059.31   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "6             75         8   9.638554  \n",
      "18             4         2  33.333333  \n",
      "19            12         9  42.857143  \n",
      "22             8         0   0.000000  \n",
      "27            10         0   0.000000  \n",
      "31             8         5  38.461538  \n",
      "36            13         0   0.000000  \n",
      "37             2         0   0.000000  \n",
      "40            13         0   0.000000  \n",
      "45            10         2  16.666667  \n",
      "46            16        11  40.740741  \n",
      "51             5         0   0.000000  \n",
      "56            14         0   0.000000  \n",
      "58            10         0   0.000000  \n",
      "59            10         0   0.000000  \n",
      "61             3         0   0.000000  \n",
      "63            13         0   0.000000  \n",
      "66            24         2   7.692308  \n",
      "71             4         0   0.000000  \n",
      "72             3         0   0.000000  \n",
      "94             6         0   0.000000  \n",
      "100            8         0   0.000000  \n",
      "116            2         2  50.000000  \n",
      "121           25         2   7.407407  \n",
      "122           29         3   9.375000  \n",
      "125           25         0   0.000000  \n",
      "131            4         0   0.000000  \n",
      "133            1         0   0.000000  \n",
      "152            3         0   0.000000  \n",
      "167            5         2  28.571429  \n",
      "...          ...       ...        ...  \n",
      "328333        17         7  29.166667  \n",
      "328337        18         0   0.000000  \n",
      "328340         7         0   0.000000  \n",
      "328342        22         0   0.000000  \n",
      "328355        10         0   0.000000  \n",
      "328363         2         1  33.333333  \n",
      "328367         5         0   0.000000  \n",
      "328368         3         1  25.000000  \n",
      "328377         1         0   0.000000  \n",
      "328378         4         0   0.000000  \n",
      "328397         5         0   0.000000  \n",
      "328409         8         1  11.111111  \n",
      "328421         3         0   0.000000  \n",
      "328424         7         0   0.000000  \n",
      "328425       161         0   0.000000  \n",
      "328430         7         0   0.000000  \n",
      "328435        55         0   0.000000  \n",
      "328440        27         0   0.000000  \n",
      "328446        19         0   0.000000  \n",
      "328448        11        14  56.000000  \n",
      "328455         8         0   0.000000  \n",
      "328459         8         0   0.000000  \n",
      "328470         3         0   0.000000  \n",
      "328495        16         0   0.000000  \n",
      "328498        15         0   0.000000  \n",
      "328513         2         0   0.000000  \n",
      "328516        24         0   0.000000  \n",
      "328522         4         0   0.000000  \n",
      "328542        45         0   0.000000  \n",
      "328552         4         0   0.000000  \n",
      "\n",
      "[52748 rows x 22 columns],         ListingId  借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "16        1518801  4913    12  24.0  2015-01-01    D     普通    否  26  男   \n",
      "35        1549891  4940    12  22.0  2015-01-02    C     普通    否  24  男   \n",
      "39        1551331  4691    12  18.0  2015-01-04    B     普通    否  45  男   \n",
      "62        1569871  4444    12  22.0  2015-01-02    E     普通    否  39  男   \n",
      "64        1571061  4890    12  22.0  2015-01-04    D     普通    否  24  男   \n",
      "78        1578731  4260    10  18.0  2015-01-07    C     普通    否  26  女   \n",
      "79        1579131  4500    12  20.0  2015-01-01    C     普通    否  29  男   \n",
      "81        1579591  4311    10  20.0  2015-01-04    C     电商    否  27  女   \n",
      "86        1581351  4000     7  18.0  2015-01-04    C     普通    否  36  男   \n",
      "88        1581371  4000    12  20.0  2015-01-07    D     普通    否  28  男   \n",
      "95        1585151  4525    12  22.0  2015-01-05    B     普通    否  30  男   \n",
      "98        1586211  4500    12  20.0  2015-01-07    C     普通    否  29  男   \n",
      "101       1586721  4450    12  24.0  2015-01-05    D     普通    否  27  男   \n",
      "108       1590361  4284    12  20.0  2015-01-07    D     普通    否  31  女   \n",
      "111       1592951  4149    12  22.0  2015-01-05    D     普通    否  26  男   \n",
      "120       1595991  4500    12  20.0  2015-01-07    D     普通    否  34  男   \n",
      "124       1599181  4353     6  18.0  2015-01-09    C     普通    否  28  男   \n",
      "127       1600291  4500    12  24.0  2015-01-07    F     普通    否  31  男   \n",
      "128       1601641  4721    12  22.0  2015-01-06    E     普通    否  23  男   \n",
      "129       1602331  4500    12  22.0  2015-01-08    E     普通    否  25  男   \n",
      "170       1621661  4601    12  22.0  2015-01-07    D     普通    否  24  女   \n",
      "171       1622351  4944     6  18.0  2015-01-09    C     普通    否  37  男   \n",
      "174       1622901  4000     6  18.0  2015-01-09    C     普通    否  41  男   \n",
      "187       1629111  4420     6  16.0  2015-01-07    C     电商    否  25  女   \n",
      "191       1630491  4200     6  18.0  2015-01-09    C     普通    否  30  男   \n",
      "201       1633051  4189    12  24.0  2015-01-09    F     普通    否  25  男   \n",
      "210       1636121  4881     6  18.0  2015-01-14    C     普通    否  48  男   \n",
      "215       1638771  4510     6  18.0  2015-01-14    C     普通    否  30  男   \n",
      "245       1652081  4300     6  18.0  2015-01-12    C     普通    否  38  男   \n",
      "248       1654671  4000     6  18.0  2015-01-14    D     普通    否  23  男   \n",
      "...           ...   ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328304   32803021  4503     6  20.0  2017-01-30    D     普通    否  29  男   \n",
      "328339   32804971  4264    12  20.0  2017-01-30    C     其他    否  26  女   \n",
      "328341   32805021  4212     6  20.0  2017-01-30    D     普通    否  23  女   \n",
      "328345   32805101  4000     6  20.0  2017-01-30    D     其他    否  32  男   \n",
      "328346   32805111  4000     6  20.0  2017-01-30    C     普通    否  50  男   \n",
      "328354   32805301  4146     6  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328357   32805341  4682     6  20.0  2017-01-30    C     普通    否  28  女   \n",
      "328358   32805361  4000    12  20.0  2017-01-30    C     其他    否  25  男   \n",
      "328361   32805431  4000     6  20.0  2017-01-30    C     普通    否  24  男   \n",
      "328371   32806081  4006    12  20.0  2017-01-30    C     普通    否  30  男   \n",
      "328375   32806271  4000     7  20.0  2017-01-30    C     其他    否  28  男   \n",
      "328380   32806451  4168    12  22.0  2017-01-30    D     其他    否  28  男   \n",
      "328385   32806581  4842    12  20.0  2017-01-30    C     普通    否  23  男   \n",
      "328393   32807141  4402    12  22.0  2017-01-30    C     普通    否  24  男   \n",
      "328401   32807441  4000    12  22.0  2017-01-30    D     其他    否  28  男   \n",
      "328403   32807591  4310    12  20.0  2017-01-30    C     其他    否  27  男   \n",
      "328423   32808831  4000    12  22.0  2017-01-30    D     普通    否  25  男   \n",
      "328429   32809061  4931     6  20.0  2017-01-30    C     普通    否  25  男   \n",
      "328438   32809811  4134     6  20.0  2017-01-30    B     其他    否  28  男   \n",
      "328441   32809921  4000     6  20.0  2017-01-30    C     其他    否  22  男   \n",
      "328456   32811271  4006    12  22.0  2017-01-30    D  APP闪电    否  25  男   \n",
      "328458   32811341  4022     6  20.0  2017-01-30    C     其他    否  31  男   \n",
      "328463   32811681  4180    12  22.0  2017-01-30    C     普通    否  35  男   \n",
      "328466   32811931  4202     9  20.0  2017-01-30    C     普通    否  33  女   \n",
      "328467   32811991  4565    12  22.0  2017-01-30    D     普通    否  33  男   \n",
      "328504   32815111  4201    12  22.0  2017-01-30    D  APP闪电    否  45  男   \n",
      "328506   32815221  4782    12  20.0  2017-01-30    C     其他    否  23  男   \n",
      "328507   32815401  4497    12  22.0  2017-01-30    C     其他    否  38  女   \n",
      "328512   32815861  4000    12  22.0  2017-01-30    D  APP闪电    否  31  男   \n",
      "328523   32817151  4564     6  20.0  2017-01-30    C     其他    否  30  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  \\\n",
      "16        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "35        ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "39        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  12788.0   7685.42   \n",
      "62        ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "64        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  14747.0   6703.83   \n",
      "78        ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0   1739.84   \n",
      "79        ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0    640.29   \n",
      "81        ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6147.0   3012.83   \n",
      "86        ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0   1739.84   \n",
      "88        ...      未成功认证  未成功认证  未成功认证  未成功认证        3  10196.0   5944.84   \n",
      "95        ...       成功认证   成功认证  未成功认证  未成功认证        5  25180.0   5198.01   \n",
      "98        ...      未成功认证  未成功认证  未成功认证  未成功认证        4  18858.0   4765.27   \n",
      "101       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "108       ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9499.0   5747.85   \n",
      "111       ...      未成功认证   成功认证  未成功认证  未成功认证        2   6140.0   2994.38   \n",
      "120       ...       成功认证  未成功认证  未成功认证  未成功认证        2   6500.0   3252.03   \n",
      "124       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1313.46   \n",
      "127       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1297.26   \n",
      "128       ...       成功认证  未成功认证  未成功认证  未成功认证        4  13314.0   3363.63   \n",
      "129       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0   3400.78   \n",
      "170       ...       成功认证  未成功认证  未成功认证  未成功认证        4  12585.0   5163.72   \n",
      "171       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6500.0   2356.49   \n",
      "174       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "187       ...       成功认证  未成功认证  未成功认证  未成功认证        2  13290.0   3573.17   \n",
      "191       ...      未成功认证   成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "201       ...       成功认证  未成功认证  未成功认证  未成功认证        1   3000.0   1297.26   \n",
      "210       ...       成功认证  未成功认证  未成功认证  未成功认证        7  25477.0   4928.70   \n",
      "215       ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7060.0      0.00   \n",
      "245       ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3000.0      0.00   \n",
      "248       ...       成功认证  未成功认证  未成功认证  未成功认证        6  22250.0   4096.40   \n",
      "...       ...        ...    ...    ...    ...      ...      ...       ...   \n",
      "328304    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6481.0   4485.91   \n",
      "328339    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  13026.0   7735.01   \n",
      "328341    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7475.0   5287.97   \n",
      "328345    ...      未成功认证   成功认证  未成功认证  未成功认证        3  10100.0   3000.00   \n",
      "328346    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6642.0   3999.75   \n",
      "328354    ...      未成功认证   成功认证  未成功认证  未成功认证        1   5500.0   3353.05   \n",
      "328357    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   7318.0   3318.00   \n",
      "328358    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   4000.0   2544.29   \n",
      "328361    ...      未成功认证  未成功认证  未成功认证  未成功认证        6  12882.0      0.00   \n",
      "328371    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   9518.0   6493.75   \n",
      "328375    ...      未成功认证   成功认证  未成功认证  未成功认证        3   7839.0   3699.30   \n",
      "328380    ...      未成功认证   成功认证  未成功认证  未成功认证        2   8951.0   4831.58   \n",
      "328385    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   6000.0   3658.50   \n",
      "328393    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   2100.0   1598.27   \n",
      "328401    ...      未成功认证   成功认证   成功认证  未成功认证        8  16605.0   5799.99   \n",
      "328403    ...      未成功认证   成功认证  未成功认证  未成功认证        3  11457.0   6169.88   \n",
      "328423    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   7300.0   3000.00   \n",
      "328429    ...       成功认证   成功认证  未成功认证  未成功认证       12  64358.0  33767.04   \n",
      "328438    ...      未成功认证   成功认证  未成功认证  未成功认证        3  15592.0   7085.83   \n",
      "328441    ...      未成功认证  未成功认证  未成功认证  未成功认证        4  17000.0  15552.32   \n",
      "328456    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   9944.0   2893.38   \n",
      "328458    ...      未成功认证   成功认证  未成功认证  未成功认证        7  30677.0  15944.82   \n",
      "328463    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   5000.0   2320.48   \n",
      "328466    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   5500.0   3798.18   \n",
      "328467    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   5500.0   2935.20   \n",
      "328504    ...      未成功认证  未成功认证  未成功认证  未成功认证        2  10500.0   6098.62   \n",
      "328506    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   1600.0   1217.74   \n",
      "328507    ...      未成功认证   成功认证  未成功认证  未成功认证        1   4200.0   1502.89   \n",
      "328512    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   4000.0      0.00   \n",
      "328523    ...      未成功认证  未成功认证  未成功认证  未成功认证        1   3200.0   2435.46   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "16             2         0   0.000000  \n",
      "35             4         0   0.000000  \n",
      "39            17         0   0.000000  \n",
      "62             4         0   0.000000  \n",
      "64            19         0   0.000000  \n",
      "78             3         0   0.000000  \n",
      "79             8         0   0.000000  \n",
      "81             7         0   0.000000  \n",
      "86             3         0   0.000000  \n",
      "88            16         0   0.000000  \n",
      "95            24         4  14.285714  \n",
      "98            15         0   0.000000  \n",
      "101            4         0   0.000000  \n",
      "108           14         1   6.666667  \n",
      "111            7         0   0.000000  \n",
      "120            7         0   0.000000  \n",
      "124            4         0   0.000000  \n",
      "127            4         3  42.857143  \n",
      "128           25         0   0.000000  \n",
      "129            6         0   0.000000  \n",
      "170           21         0   0.000000  \n",
      "171            6         0   0.000000  \n",
      "174            1         0   0.000000  \n",
      "187            5         0   0.000000  \n",
      "191            3         0   0.000000  \n",
      "201            5         2  28.571429  \n",
      "210           33         1   2.941176  \n",
      "215            3         0   0.000000  \n",
      "245            1         0   0.000000  \n",
      "248           31         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "328304        12         0   0.000000  \n",
      "328339        21         0   0.000000  \n",
      "328341         7         1  12.500000  \n",
      "328345        11        13  54.166667  \n",
      "328346         4         0   0.000000  \n",
      "328354         5         0   0.000000  \n",
      "328357         5         1  16.666667  \n",
      "328358        14         0   0.000000  \n",
      "328361        46         0   0.000000  \n",
      "328371        15         0   0.000000  \n",
      "328375        11         5  31.250000  \n",
      "328380        10         1   9.090909  \n",
      "328385         8         0   0.000000  \n",
      "328393         3         0   0.000000  \n",
      "328401        36         9  20.000000  \n",
      "328403        15         0   0.000000  \n",
      "328423        22         2   8.333333  \n",
      "328429        47         1   2.083333  \n",
      "328438        21         0   0.000000  \n",
      "328441         3         0   0.000000  \n",
      "328456        16         0   0.000000  \n",
      "328458        25         0   0.000000  \n",
      "328463         6         1  14.285714  \n",
      "328466         4         0   0.000000  \n",
      "328467        19         0   0.000000  \n",
      "328504         8         0   0.000000  \n",
      "328506         2         1  33.333333  \n",
      "328507         6         2  25.000000  \n",
      "328512         6         0   0.000000  \n",
      "328523         3         0   0.000000  \n",
      "\n",
      "[29166 rows x 22 columns],         ListingId  借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "15        1080421  5250     6  18.0  2015-05-27    C     电商    否  25  男   \n",
      "20        1537391  5161    12  24.0  2015-01-02    F     普通    否  35  男   \n",
      "50        1558481  5000    10  18.0  2015-01-07    C     普通    否  26  男   \n",
      "68        1573151  5298    12  24.0  2015-01-01    D     普通    否  27  男   \n",
      "69        1573191  5000    12  20.0  2015-01-07    D     普通    否  23  男   \n",
      "85        1580881  5000    12  19.0  2015-01-05    C     普通    否  25  男   \n",
      "105       1588621  5662    12  18.0  2015-01-09    C     普通    否  24  女   \n",
      "110       1592201  5000     6  14.0  2015-01-04    A     普通    否  32  女   \n",
      "114       1594791  5200     6  18.0  2015-01-05    C     电商    否  31  男   \n",
      "126       1600131  5595     6  18.0  2015-01-04    C     普通    否  35  男   \n",
      "146       1607961  5000    10  16.0  2015-01-05    B     普通    否  37  男   \n",
      "154       1612081  5000     3  14.0  2015-01-06    A     普通    否  38  男   \n",
      "205       1634121  5731    12  20.0  2015-01-20    D     普通    否  50  女   \n",
      "246       1652401  5000    12  20.0  2015-01-13    B     普通    否  25  男   \n",
      "247       1652521  5591    12  20.0  2015-01-22    D     普通    否  27  男   \n",
      "294       1672691  5625    12  22.0  2015-01-17    D     普通    否  42  男   \n",
      "319       1678701  5000     3  14.0  2015-01-19    A     普通    否  33  男   \n",
      "331       1682391  5454    12  22.0  2015-01-17    D     普通    否  27  男   \n",
      "346       1686461  5800     6  18.0  2015-01-16    C     普通    否  28  男   \n",
      "361       1689971  5050     6  18.0  2015-01-23    C     普通    否  42  男   \n",
      "362       1690131  5041     6  18.0  2015-01-23    C     普通    否  31  男   \n",
      "363       1690211  5722     6  16.0  2015-01-18    A     普通    否  29  男   \n",
      "383       1695641  5836     6  18.0  2015-01-23    C     普通    否  31  男   \n",
      "403       1703841  5800    12  20.0  2015-01-26    D     普通    否  23  男   \n",
      "420       1707611  5360    12  22.0  2015-01-30    E     普通    否  27  男   \n",
      "428       1710551  5800    12  20.0  2015-01-30    C     普通    否  29  男   \n",
      "441       1714781  5800    12  20.0  2015-01-26    C     普通    否  26  女   \n",
      "445       1715541  5042    12  24.0  2015-01-28    F     普通    否  24  男   \n",
      "453       1717031  5836    12  20.0  2015-01-30    C     普通    否  33  女   \n",
      "457       1717391  5100     6  18.0  2015-01-28    C     普通    否  26  男   \n",
      "...           ...   ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "328190   32794681  5021     6  20.0  2017-01-30    C     普通    否  38  男   \n",
      "328239   32798701  5000    12  20.0  2017-01-30    C     普通    否  30  男   \n",
      "328255   32799811  5900     6  16.0  2017-01-30    A  APP闪电    否  38  女   \n",
      "328307   32803171  5000    12  20.0  2017-01-30    A     其他    否  25  男   \n",
      "328331   32804601  5675     6  20.0  2017-01-30    C     普通    否  30  男   \n",
      "328344   32805071  5806    12  20.0  2017-01-30    A     普通    否  28  女   \n",
      "328348   32805141  5436    12  22.0  2017-01-30    D     其他    否  27  男   \n",
      "328351   32805271  5000    10  20.0  2017-01-30    C     其他    否  35  男   \n",
      "328366   32805671  5642    12  20.0  2017-01-30    C     普通    否  25  女   \n",
      "328370   32806041  5903     6  20.0  2017-01-30    C     普通    否  47  男   \n",
      "328379   32806411  5327    12  22.0  2017-01-30    C     普通    否  35  男   \n",
      "328384   32806551  5000    12  20.0  2017-01-30    C     普通    否  28  男   \n",
      "328399   32807381  5982    12  20.0  2017-01-30    C     普通    否  38  女   \n",
      "328408   32807801  5051    12  20.0  2017-01-30    C     普通    否  27  男   \n",
      "328413   32808091  5000    12  22.0  2017-01-30    D     其他    否  31  女   \n",
      "328414   32808131  5477    12  20.0  2017-01-30    C     其他    否  36  男   \n",
      "328416   32808181  5482    12  22.0  2017-01-30    C     普通    否  29  男   \n",
      "328437   32809801  5000     8  20.0  2017-01-30    C     其他    否  27  女   \n",
      "328445   32810171  5500    12  22.0  2017-01-30    D     普通    否  34  男   \n",
      "328454   32810981  5630     6  20.0  2017-01-30    C     普通    否  34  女   \n",
      "328460   32811441  5900    12  20.0  2017-01-30    C  APP闪电    否  35  男   \n",
      "328475   32812651  5089    12  20.0  2017-01-30    C     普通    否  28  男   \n",
      "328484   32813311  5803     6  20.0  2017-01-30    C     普通    否  47  男   \n",
      "328488   32813601  5089     6  20.0  2017-01-30    C  APP闪电    否  32  男   \n",
      "328497   32814351  5000     6  20.0  2017-01-30    C     其他    否  39  女   \n",
      "328505   32815181  5000    12  22.0  2017-01-30    D     普通    否  41  男   \n",
      "328524   32817221  5100    12  20.0  2017-01-30    B     普通    否  24  男   \n",
      "328529   32817621  5000    12  18.0  2017-01-30    B     其他    否  24  女   \n",
      "328543   32818851  5804    12  20.0  2017-01-30    C     其他    否  44  男   \n",
      "328545   32818901  5008    12  20.0  2017-01-30    C     其他    否  28  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  \\\n",
      "15        ...       成功认证  未成功认证  未成功认证   成功认证        7  379000.0  10745.88   \n",
      "20        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10128.0   3284.98   \n",
      "50        ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6000.0    786.87   \n",
      "68        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "69        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0    896.34   \n",
      "85        ...      未成功认证   成功认证  未成功认证  未成功认证        5   20300.0   2940.51   \n",
      "105       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0    880.34   \n",
      "110       ...       成功认证   成功认证  未成功认证  未成功认证        4   20000.0   5785.68   \n",
      "114       ...       成功认证  未成功认证  未成功认证  未成功认证       15   85490.0   6715.80   \n",
      "126       ...       成功认证   成功认证  未成功认证  未成功认证        7   33100.0   4404.56   \n",
      "146       ...       成功认证  未成功认证  未成功认证  未成功认证        6   29600.0   6449.70   \n",
      "154       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "205       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "246       ...      未成功认证  未成功认证  未成功认证  未成功认证        5   29200.0   8130.56   \n",
      "247       ...       成功认证  未成功认证  未成功认证  未成功认证        3   11200.0   2855.34   \n",
      "294       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "319       ...       成功认证  未成功认证  未成功认证  未成功认证        7   33500.0   2553.29   \n",
      "331       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0    546.49   \n",
      "346       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0   2164.08   \n",
      "361       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "362       ...       成功认证  未成功认证  未成功认证  未成功认证        2    7600.0      0.00   \n",
      "363       ...      未成功认证   成功认证  未成功认证  未成功认证        2    7394.0      0.00   \n",
      "383       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0   1739.84   \n",
      "403       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0   1739.84   \n",
      "420       ...      未成功认证  未成功认证  未成功认证  未成功认证        6   25200.0   4887.40   \n",
      "428       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   2164.08   \n",
      "441       ...      未成功认证   成功认证  未成功认证  未成功认证        1    3000.0   1739.84   \n",
      "445       ...      未成功认证  未成功认证  未成功认证  未成功认证        2    6339.0   2250.71   \n",
      "453       ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   1739.84   \n",
      "457       ...      未成功认证   成功认证  未成功认证  未成功认证        5   19200.0      0.00   \n",
      "...       ...        ...    ...    ...    ...      ...       ...       ...   \n",
      "328190    ...      未成功认证   成功认证  未成功认证  未成功认证        1    2600.0   1978.82   \n",
      "328239    ...      未成功认证   成功认证  未成功认证  未成功认证        2    6000.0   3561.21   \n",
      "328255    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    5600.0      0.00   \n",
      "328307    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1500.0    896.68   \n",
      "328331    ...      未成功认证   成功认证  未成功认证  未成功认证        4   31183.0  12324.77   \n",
      "328344    ...      未成功认证   成功认证  未成功认证  未成功认证        2    8006.0   1393.78   \n",
      "328348    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   16112.0   3063.32   \n",
      "328351    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12400.0   5148.48   \n",
      "328366    ...      未成功认证   成功认证  未成功认证  未成功认证        4   16560.0   5857.68   \n",
      "328370    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3500.0    596.71   \n",
      "328379    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3300.0   1672.58   \n",
      "328384    ...      未成功认证   成功认证  未成功认证  未成功认证        4   11000.0   7634.85   \n",
      "328399    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   1018.31   \n",
      "328408    ...      未成功认证   成功认证  未成功认证  未成功认证        9   23423.0  12948.79   \n",
      "328413    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    7888.0   4016.62   \n",
      "328414    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2000.0   1522.18   \n",
      "328416    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0   1018.31   \n",
      "328437    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    7000.0   1420.82   \n",
      "328445    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1500.0      0.00   \n",
      "328454    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1800.0   1369.96   \n",
      "328460    ...      未成功认证  未成功认证  未成功认证  未成功认证        6    8496.0      0.00   \n",
      "328475    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2000.0    910.63   \n",
      "328484    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    5000.0   1697.17   \n",
      "328488    ...      未成功认证   成功认证  未成功认证  未成功认证        1    7000.0   2410.89   \n",
      "328497    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2000.0   1359.71   \n",
      "328505    ...      未成功认证  未成功认证  未成功认证  未成功认证        2    5000.0    384.47   \n",
      "328524    ...      未成功认证   成功认证  未成功认证  未成功认证        2    6164.0   4301.54   \n",
      "328529    ...      未成功认证   成功认证   成功认证  未成功认证       11   39730.0  18516.42   \n",
      "328543    ...      未成功认证   成功认证  未成功认证  未成功认证        3   12421.0   5395.26   \n",
      "328545    ...      未成功认证  未成功认证  未成功认证  未成功认证        4   10500.0   7727.37   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "15            31         2   6.060606  \n",
      "20            17         9  34.615385  \n",
      "50            13         3  18.750000  \n",
      "68             3         0   0.000000  \n",
      "69             5         0   0.000000  \n",
      "85            13         3  18.750000  \n",
      "105            2         3  60.000000  \n",
      "110           29         0   0.000000  \n",
      "114           40         3   6.976744  \n",
      "126           13         0   0.000000  \n",
      "146           29         0   0.000000  \n",
      "154            1         0   0.000000  \n",
      "205            3         0   0.000000  \n",
      "246           36         0   0.000000  \n",
      "247           13         1   7.142857  \n",
      "294            3         0   0.000000  \n",
      "319           34         7  17.073171  \n",
      "331           10         0   0.000000  \n",
      "346            2         0   0.000000  \n",
      "361            2         0   0.000000  \n",
      "362            2         0   0.000000  \n",
      "363            5         0   0.000000  \n",
      "383            3         0   0.000000  \n",
      "403            3         0   0.000000  \n",
      "420           20         1   4.761905  \n",
      "428            2         0   0.000000  \n",
      "441            2         1  33.333333  \n",
      "445           10         6  37.500000  \n",
      "453            3         0   0.000000  \n",
      "457            6         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "328190         3         0   0.000000  \n",
      "328239        11         0   0.000000  \n",
      "328255         6         0   0.000000  \n",
      "328307         5         0   0.000000  \n",
      "328331        22         0   0.000000  \n",
      "328344         4        12  75.000000  \n",
      "328348        23         0   0.000000  \n",
      "328351        20         1   4.761905  \n",
      "328366        13         9  40.909091  \n",
      "328370         5         0   0.000000  \n",
      "328379         3         0   0.000000  \n",
      "328384        11         0   0.000000  \n",
      "328399         4         0   0.000000  \n",
      "328408        45         4   8.163265  \n",
      "328413         6         0   0.000000  \n",
      "328414         3         0   0.000000  \n",
      "328416         4         0   0.000000  \n",
      "328437        20         1   4.761905  \n",
      "328445         5         1  16.666667  \n",
      "328454         3         0   0.000000  \n",
      "328460        66         0   0.000000  \n",
      "328475         6         1  14.285714  \n",
      "328484         4         0   0.000000  \n",
      "328488         4         0   0.000000  \n",
      "328497         4         0   0.000000  \n",
      "328505        11         2  15.384615  \n",
      "328524         5         3  37.500000  \n",
      "328529        66         0   0.000000  \n",
      "328543        15         1   6.250000  \n",
      "328545        14         0   0.000000  \n",
      "\n",
      "[17450 rows x 22 columns],         ListingId    借款金额  借款期限  借款利率      借款成功日期 初始评级   借款类型 是否首标  年龄 性别  \\\n",
      "0          126541   18000    12  18.0  2015-05-04    C     其他    否  35  男   \n",
      "1          133291    9453    12  20.0  2015-03-16    D     其他    否  34  男   \n",
      "2          142421   27000    24  20.0  2016-04-26    E     普通    否  41  男   \n",
      "3          149711   25000    12  18.0  2015-03-30    C     其他    否  34  男   \n",
      "4          152141   20000     6  16.0  2015-01-22    C     电商    否  24  男   \n",
      "5          162641   20000    12  14.0  2015-03-25    A     普通    否  36  男   \n",
      "7          175451   20000    12  18.0  2016-03-19    B     普通    否  32  男   \n",
      "8          182261   25000    12  16.0  2015-03-21    B     其他    否  33  女   \n",
      "9          193831   10475     6  18.0  2015-04-15    C     电商    否  25  男   \n",
      "10         199461   25000    12  20.0  2015-11-29    E     普通    否  29  男   \n",
      "11         209191   20000    12  20.0  2015-11-28    E     普通    否  33  男   \n",
      "12         209381   30000    24  16.0  2015-06-28    E     其他    否  30  男   \n",
      "13         223081   26000    12  20.0  2016-06-28    E     普通    否  35  男   \n",
      "14         528911   11000    12  20.0  2015-03-10    C     其他    否  47  男   \n",
      "21        1537661    8000    12  20.0  2015-01-04    C     普通    否  39  男   \n",
      "23        1540111   12778    12  20.0  2015-01-04    D     普通    否  26  男   \n",
      "24        1541631   10000    12  20.0  2015-01-04    D     普通    否  38  男   \n",
      "25        1541641   11578    12  20.0  2015-01-04    D     其他    否  27  男   \n",
      "26        1541761   10000    12  20.0  2015-01-04    D     普通    否  29  男   \n",
      "28        1542681   13083    12  18.0  2015-01-04    C     普通    否  46  男   \n",
      "29        1542821   11748    12  18.0  2015-01-04    C     普通    否  29  女   \n",
      "30        1546771   12000    12  18.0  2015-01-04    C     普通    否  27  男   \n",
      "32        1548231    8000    12  20.0  2015-01-04    D     其他    否  27  男   \n",
      "33        1548521   10053    12  18.0  2015-01-07    C     普通    否  34  男   \n",
      "38        1551311    8500    12  20.0  2015-01-04    C     普通    否  31  男   \n",
      "41        1551961    8972    12  18.0  2015-01-06    C     普通    否  31  女   \n",
      "42        1553151    8000    12  18.0  2015-01-07    C     普通    否  36  男   \n",
      "43        1553501  400000     6  14.0  2015-01-03    B     电商    否  44  女   \n",
      "44        1554311    9000     6  18.0  2015-01-04    D     普通    否  25  男   \n",
      "47        1557211   10660    12  20.0  2015-01-05    C     普通    否  27  男   \n",
      "...           ...     ...   ...   ...         ...  ...    ...  ...  .. ..   \n",
      "327967   32782201    6502    12  18.0  2017-01-30    B  APP闪电    否  38  女   \n",
      "327987   32783451    6183    12  22.0  2017-01-30    D  APP闪电    否  24  女   \n",
      "327993   32783651    6632    12  20.0  2017-01-30    C     其他    否  34  男   \n",
      "328083   32788401    7660    12  20.0  2017-01-30    C     其他    否  42  男   \n",
      "328087   32788621    6000     6  20.0  2017-01-30    C     普通    否  21  男   \n",
      "328117   32790211   11749    12  22.0  2017-01-30    D  APP闪电    否  28  男   \n",
      "328126   32790781   12500    12  20.0  2017-01-30    C     其他    否  26  男   \n",
      "328141   32791291    6800    12  18.0  2017-01-30    B  APP闪电    否  26  男   \n",
      "328161   32792581    8211     6  20.0  2017-01-30    D     普通    否  35  女   \n",
      "328176   32793341    7308    11  16.0  2017-01-30    A     其他    否  26  男   \n",
      "328177   32793521    6029    12  20.0  2017-01-30    C  APP闪电    否  30  男   \n",
      "328223   32797061   12000     6  20.0  2017-01-30    C     其他    否  27  男   \n",
      "328258   32800261   10000    12  20.0  2017-01-30    D     其他    否  24  男   \n",
      "328263   32800441    7440    12  20.0  2017-01-30    C     普通    否  27  男   \n",
      "328276   32801351   10000    12  20.0  2017-01-30    D     普通    否  25  女   \n",
      "328284   32801781    6800    12  22.0  2017-01-30    D  APP闪电    否  34  男   \n",
      "328292   32802361    6083     6  20.0  2017-01-30    A     其他    否  33  男   \n",
      "328294   32802401    6152     6  18.0  2017-01-30    B     其他    否  42  男   \n",
      "328313   32803901    6824    12  22.0  2017-01-30    D  APP闪电    否  27  男   \n",
      "328328   32804381   11200    12  20.0  2017-01-30    C  APP闪电    否  36  男   \n",
      "328338   32804951    6975    11  20.0  2017-01-30    C     其他    否  33  男   \n",
      "328405   32807751    7628    12  18.0  2017-01-30    B     其他    否  24  男   \n",
      "328411   32808011   11577     6  20.0  2017-01-30    C     其他    否  23  男   \n",
      "328419   32808391    6036    11  20.0  2017-01-30    C     其他    否  28  男   \n",
      "328432   32809531    7133     3  16.0  2017-01-30    A     普通    否  38  女   \n",
      "328464   32811881    9500     9  20.0  2017-01-30    C     其他    否  33  女   \n",
      "328526   32817361    7354    12  20.0  2017-01-30    C     普通    否  25  男   \n",
      "328544   32818871    6880     6  20.0  2017-01-30    C     其他    否  28  男   \n",
      "328549   32819381    7000    12  20.0  2017-01-30    C     其他    否  22  男   \n",
      "328551   32819511    6406    12  20.0  2017-01-30    C     其他    否  33  男   \n",
      "\n",
      "          ...       视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数  历史成功借款金额     总待还本金  \\\n",
      "0         ...       成功认证  未成功认证  未成功认证  未成功认证       11   40326.0   8712.73   \n",
      "1         ...      未成功认证  未成功认证  未成功认证  未成功认证        4   14500.0   7890.64   \n",
      "2         ...      未成功认证  未成功认证  未成功认证  未成功认证        5   21894.0  11726.32   \n",
      "3         ...       成功认证  未成功认证  未成功认证  未成功认证        6   36190.0   9703.41   \n",
      "4         ...       成功认证  未成功认证  未成功认证  未成功认证       13   77945.0      0.00   \n",
      "5         ...       成功认证  未成功认证  未成功认证  未成功认证        7   35622.0      0.00   \n",
      "7         ...       成功认证  未成功认证  未成功认证  未成功认证        7   35000.0   4078.61   \n",
      "8         ...       成功认证  未成功认证  未成功认证  未成功认证        7   42530.0   7418.35   \n",
      "9         ...       成功认证  未成功认证  未成功认证  未成功认证        9  107000.0      0.00   \n",
      "10        ...       成功认证  未成功认证  未成功认证  未成功认证       12   71701.0   8109.78   \n",
      "11        ...       成功认证  未成功认证  未成功认证  未成功认证       12   79566.0      0.00   \n",
      "12        ...       成功认证  未成功认证  未成功认证  未成功认证        7   39000.0      0.00   \n",
      "13        ...       成功认证  未成功认证   成功认证  未成功认证       12   54122.0   8388.58   \n",
      "14        ...      未成功认证  未成功认证  未成功认证  未成功认证        5   17809.0   3589.14   \n",
      "21        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "23        ...      未成功认证  未成功认证  未成功认证  未成功认证        4   12700.0   1703.56   \n",
      "24        ...       成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "25        ...       成功认证  未成功认证  未成功认证  未成功认证        4   20366.0   8378.53   \n",
      "26        ...      未成功认证   成功认证  未成功认证  未成功认证        3    9500.0   5452.42   \n",
      "28        ...       成功认证   成功认证  未成功认证  未成功认证        5   22100.0   6015.72   \n",
      "29        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12000.0   6766.82   \n",
      "30        ...      未成功认证   成功认证  未成功认证  未成功认证        6   23000.0   7633.48   \n",
      "32        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "33        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   10000.0   4393.83   \n",
      "38        ...       成功认证   成功认证  未成功认证  未成功认证        3   11900.0      0.00   \n",
      "41        ...      未成功认证  未成功认证  未成功认证  未成功认证        3   12200.0   4796.70   \n",
      "42        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0    786.71   \n",
      "43        ...       成功认证  未成功认证  未成功认证  未成功认证        1  350000.0      0.00   \n",
      "44        ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "47        ...       成功认证   成功认证  未成功认证  未成功认证        3   11800.0   5578.70   \n",
      "...       ...        ...    ...    ...    ...      ...       ...       ...   \n",
      "327967    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    5000.0   4207.57   \n",
      "327987    ...      未成功认证  未成功认证  未成功认证  未成功认证        7   13800.0   3116.86   \n",
      "327993    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   14756.0   7367.95   \n",
      "328083    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3000.0      0.00   \n",
      "328087    ...      未成功认证  未成功认证  未成功认证  未成功认证        6   35300.0      0.00   \n",
      "328117    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2000.0    350.17   \n",
      "328126    ...      未成功认证   成功认证   成功认证  未成功认证        8   63601.0      0.00   \n",
      "328141    ...      未成功认证   成功认证  未成功认证  未成功认证        4   14000.0   7233.52   \n",
      "328161    ...      未成功认证   成功认证  未成功认证  未成功认证        4   18495.0   7752.61   \n",
      "328176    ...      未成功认证  未成功认证  未成功认证  未成功认证        2   13500.0   4101.06   \n",
      "328177    ...      未成功认证   成功认证  未成功认证  未成功认证        4   13437.0   7570.80   \n",
      "328223    ...      未成功认证   成功认证  未成功认证  未成功认证        7   71880.0      0.00   \n",
      "328258    ...      未成功认证  未成功认证  未成功认证  未成功认证        6   21448.0      0.00   \n",
      "328263    ...      未成功认证   成功认证  未成功认证  未成功认证        1    3500.0   1559.98   \n",
      "328276    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2500.0      0.00   \n",
      "328284    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3500.0      0.00   \n",
      "328292    ...      未成功认证   成功认证  未成功认证  未成功认证        2   10586.0   5416.34   \n",
      "328294    ...      未成功认证   成功认证  未成功认证  未成功认证        5   32716.0  15847.68   \n",
      "328313    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    1000.0    175.11   \n",
      "328328    ...      未成功认证  未成功认证  未成功认证  未成功认证        3   17000.0   7263.34   \n",
      "328338    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    7872.0   3312.47   \n",
      "328405    ...      未成功认证   成功认证  未成功认证  未成功认证        8   30134.0   9571.78   \n",
      "328411    ...      未成功认证  未成功认证  未成功认证  未成功认证        3    9188.0   1722.66   \n",
      "328419    ...      未成功认证   成功认证  未成功认证  未成功认证        4   11811.0   5963.91   \n",
      "328432    ...      未成功认证   成功认证  未成功认证  未成功认证        1    5500.0   1866.87   \n",
      "328464    ...      未成功认证   成功认证  未成功认证  未成功认证        2    8744.0   3865.30   \n",
      "328526    ...      未成功认证   成功认证  未成功认证  未成功认证        6   30639.0  10175.77   \n",
      "328544    ...      未成功认证   成功认证  未成功认证  未成功认证        5   19208.0  16184.84   \n",
      "328549    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    2100.0      0.00   \n",
      "328551    ...      未成功认证  未成功认证  未成功认证  未成功认证        1    3500.0   1593.59   \n",
      "\n",
      "        历史正常还款期数  历史逾期还款期数      逾期还款率  \n",
      "0             57        16  21.917808  \n",
      "1             13         1   7.142857  \n",
      "2             25         3  10.714286  \n",
      "3             41         1   2.380952  \n",
      "4            118        14  10.606061  \n",
      "5             56         0   0.000000  \n",
      "7             52         0   0.000000  \n",
      "8             41         2   4.651163  \n",
      "9             49         4   7.547170  \n",
      "10            82         0   0.000000  \n",
      "11            82         0   0.000000  \n",
      "12            27         1   3.571429  \n",
      "13            34         0   0.000000  \n",
      "14            25         2   7.407407  \n",
      "21             1         0   0.000000  \n",
      "23            19         0   0.000000  \n",
      "24             6         1  14.285714  \n",
      "25             9         0   0.000000  \n",
      "26             5         2  28.571429  \n",
      "28            19         0   0.000000  \n",
      "29            13         1   7.142857  \n",
      "30            34         4  10.526316  \n",
      "32             7         0   0.000000  \n",
      "33            12         0   0.000000  \n",
      "38            12         0   0.000000  \n",
      "41            10         0   0.000000  \n",
      "42             9         0   0.000000  \n",
      "43             6         0   0.000000  \n",
      "44             6         1  14.285714  \n",
      "47            12         0   0.000000  \n",
      "...          ...       ...        ...  \n",
      "327967         2         0   0.000000  \n",
      "327987        33         6  15.384615  \n",
      "327993        23         0   0.000000  \n",
      "328083         6         0   0.000000  \n",
      "328087        42         0   0.000000  \n",
      "328117        10         0   0.000000  \n",
      "328126        87         0   0.000000  \n",
      "328141        23         0   0.000000  \n",
      "328161        16         0   0.000000  \n",
      "328176         6         0   0.000000  \n",
      "328177        18         0   0.000000  \n",
      "328223        45         0   0.000000  \n",
      "328258        58         0   0.000000  \n",
      "328263         7         0   0.000000  \n",
      "328276         6         0   0.000000  \n",
      "328284         6         0   0.000000  \n",
      "328292        12         0   0.000000  \n",
      "328294        18         0   0.000000  \n",
      "328313        10         0   0.000000  \n",
      "328328        14         0   0.000000  \n",
      "328338        19         0   0.000000  \n",
      "328405        65         2   2.985075  \n",
      "328411        24         1   4.000000  \n",
      "328419        22         0   0.000000  \n",
      "328432         4         0   0.000000  \n",
      "328464         9         0   0.000000  \n",
      "328526        33         5  13.157895  \n",
      "328544         9         2  18.181818  \n",
      "328549        12         0   0.000000  \n",
      "328551         7         0   0.000000  \n",
      "\n",
      "[29941 rows x 22 columns])\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ListingId</th>\n",
       "      <th>借款金额</th>\n",
       "      <th>借款期限</th>\n",
       "      <th>借款利率</th>\n",
       "      <th>借款成功日期</th>\n",
       "      <th>初始评级</th>\n",
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       "      <th>是否首标</th>\n",
       "      <th>年龄</th>\n",
       "      <th>性别</th>\n",
       "      <th>...</th>\n",
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       "      <th>征信认证</th>\n",
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       "      <th>历史成功借款次数</th>\n",
       "      <th>历史成功借款金额</th>\n",
       "      <th>总待还本金</th>\n",
       "      <th>历史正常还款期数</th>\n",
       "      <th>历史逾期还款期数</th>\n",
       "      <th>逾期还款率</th>\n",
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       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
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       "      <td>24</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2016-04-26</td>\n",
       "      <td>E</td>\n",
       "      <td>普通</td>\n",
       "      <td>否</td>\n",
       "      <td>41</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
       "      <td>5</td>\n",
       "      <td>21894.0</td>\n",
       "      <td>11726.32</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
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       "      <td>25000</td>\n",
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       "      <td>34</td>\n",
       "      <td>男</td>\n",
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       "      <td>未成功认证</td>\n",
       "      <td>未成功认证</td>\n",
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      ],
      "text/plain": [
       "   ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别    ...      \\\n",
       "0     126541  18000    12  18.0  2015-05-04    C   其他    否  35  男    ...       \n",
       "1     133291   9453    12  20.0  2015-03-16    D   其他    否  34  男    ...       \n",
       "2     142421  27000    24  20.0  2016-04-26    E   普通    否  41  男    ...       \n",
       "3     149711  25000    12  18.0  2015-03-30    C   其他    否  34  男    ...       \n",
       "4     152141  20000     6  16.0  2015-01-22    C   电商    否  24  男    ...       \n",
       "\n",
       "    视频认证   学历认证   征信认证   淘宝认证 历史成功借款次数 历史成功借款金额     总待还本金  历史正常还款期数  历史逾期还款期数  \\\n",
       "0   成功认证  未成功认证  未成功认证  未成功认证       11  40326.0   8712.73        57        16   \n",
       "1  未成功认证  未成功认证  未成功认证  未成功认证        4  14500.0   7890.64        13         1   \n",
       "2  未成功认证  未成功认证  未成功认证  未成功认证        5  21894.0  11726.32        25         3   \n",
       "3   成功认证  未成功认证  未成功认证  未成功认证        6  36190.0   9703.41        41         1   \n",
       "4   成功认证  未成功认证  未成功认证  未成功认证       13  77945.0      0.00       118        14   \n",
       "\n",
       "       逾期还款率  \n",
       "0  21.917808  \n",
       "1   7.142857  \n",
       "2  10.714286  \n",
       "3   2.380952  \n",
       "4  10.606061  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amount_idx = ('0-2000', '2000-3000', '3000-4000', '4000-5000', '5000-6000', '6000+')\n",
    "amountA = LC.loc[(LC['借款金额'] > 0) & (LC['借款金额'] < 2000)]\n",
    "amountB = LC.loc[(LC['借款金额'] >= 2000) & (LC['借款金额'] < 3000)]\n",
    "amountC = LC.loc[(LC['借款金额'] >= 3000) & (LC['借款金额'] < 4000)]\n",
    "amountD = LC.loc[(LC['借款金额'] >= 4000) & (LC['借款金额'] < 5000)]\n",
    "amountE = LC.loc[(LC['借款金额'] >= 5000) & (LC['借款金额'] < 6000)]\n",
    "amountF = LC.loc[(LC['借款金额'] >= 6000)]\n",
    "amount = (amountA, amountB, amountC, amountD,amountE,amountF)\n",
    "print(amount)\n",
    "LC['逾期还款率'] = LC['历史逾期还款期数']/(LC['历史逾期还款期数']+LC['历史正常还款期数'])*100\n",
    "LC.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:38:12.072602Z",
     "start_time": "2020-07-30T13:38:11.441280Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#逾期还款率的分析图\n",
    "def depayplot(i,idx,data,xlabel,title,index):\n",
    "    depay = []\n",
    "    for a in data:\n",
    "        tmp = a[index].mean()\n",
    "        depay.append(tmp)\n",
    "    plt.subplot(2,3,i)\n",
    "    plt.bar(idx, depay)\n",
    "    for (a, b) in zip(idx, depay):\n",
    "        plt.text(a, b+0.001, '%.2f%%'% b, ha='center', va='bottom', fontsize=10)\n",
    "    plt.xlabel(xlabel)\n",
    "    plt.ylabel(index)\n",
    "    plt.title(title)\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "# index = '逾期还款率' \n",
    "# 根据初始评级对逾期还款率进行分析\n",
    "depayplot(1,level_idx,lev,'初始评级','不同初始评级客户逾期还款率','逾期还款率')\n",
    "\n",
    "# 根据年龄对逾期还款率进行分析\n",
    "depayplot(2,age_idx,age,'年龄','不同年龄客户逾期还款率','逾期还款率')\n",
    "\n",
    "# 根据借款类型对逾期还款率进行分析\n",
    "depayplot(3,kind_idx,kind,'借款类型','不同借款类型客户逾期还款率','逾期还款率')\n",
    "\n",
    "# 根据性别对逾期还款率进行分析\n",
    "depayplot(4,sex_idx,sex,'性别','不同性别客户逾期还款率','逾期还款率')\n",
    "\n",
    "# 根据借款金额对逾期还款率进行分析\n",
    "depayplot(5,amount_idx,amount,'借款金额','不同借款金额客户逾期还款率','逾期还款率')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:18:16.649867Z",
     "start_time": "2020-07-30T13:18:16.631880Z"
    }
   },
   "source": [
    "* 结论：\n",
    "\n",
    "    * 1.初始评级对于贷款者的还款能力有比较好的预测作用，EF两级反转可能是因为样本数量较少，ABCD四个等级的平均逾期还款率都比较小，而EF两级明显增大，故公司对于这两类贷款者要谨慎对待。\n",
    "\n",
    "    * 2.年龄对于逾期率的分布较为平均，25-30岁的年轻人可以重点关注。\n",
    "\n",
    "    * 3.APP闪电的逾期还款率明显低于其他三种，故公司可以多考虑与“APP闪电”借款类型的合作。\n",
    "\n",
    "    * 4.女性的逾期率高于男性，可能是由于生活中男性收入较女性高造成的。\n",
    "\n",
    "    * 5.借款金额在2000以下的逾期还款率最低，2000-3000之间的最高。可以多考虑小额贷款降低逾期风险。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.分析借款利率（借款人的初始评级、借款类型、性别、年龄、借款金额等特征）\n",
    "\n",
    "哪些客户群体更愿意接受较高的借款利率？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:41:48.873126Z",
     "start_time": "2020-07-30T13:41:48.206403Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "index1='借款利率'\n",
    "\n",
    "# 根据初始评级对借款利率进行分析\n",
    "depayplot(1,level_idx,lev,'初始评级','不同初始评级客户借款利率',index1)\n",
    "\n",
    "# 根据年龄对借款利率进行分析\n",
    "depayplot(2,age_idx,age,'年龄','不同年龄客户借款利率',index1)\n",
    "\n",
    "# 根据借款类型对借款利率进行分析\n",
    "depayplot(3,kind_idx,kind,'借款类型','不同借款类型客户借款利率',index1)\n",
    "\n",
    "# 根据性别对借款利率进行分析\n",
    "depayplot(4,sex_idx,sex,'性别','不同性别客户借款利率',index1)\n",
    "\n",
    "# 根据借款金额对借款利率进行分析\n",
    "depayplot(5,amount_idx,amount,'借款金额','不同借款金额客户借款利率',index1)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 结论：\n",
    "\n",
    "    * 1.年龄对于借款利率的分布较为平均，差异性很小。\n",
    "\n",
    "    * 2.初始评级的平均借款利率由小到大排列为ABCDFDE。\n",
    "\n",
    "    * 3.电商的借款利率明显低于其他三种。\n",
    "\n",
    "    * 4.女性所能接受的借款利率低于男性。\n",
    "\n",
    "    * 5.借款金额对于借款利率的分布较为平均，差异性很小。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 对于以上四个问题综合分析LC数据集：\n",
    "\n",
    "    * 1、“男性”、“回头客”、“中青年”是拍拍贷用户群体的主要特征。\n",
    "\n",
    "    * 2、每日公司账上需准备7,283,728元，方可保证出现当日出借金额不足的可能性小于0.1%。\n",
    "\n",
    "    * 3、“初始评级”为D的群体，借款利率与E，F大致相当，但其逾期还款率却只有E，F群体的三分之一，相同的收益水平下风险大大降低，应多发展评级为D的客户或提高其贷款额度。\n",
    "\n",
    "    * 4、通过“app闪电”贷款的逾期还款率远低于其他项，约为其他借款类型的三分之一至四分之一，而平均借款利率却和其他项相差不大，证明“app闪电”是该公司优质的合作方，其所引流来得客户质量很高，“拍拍贷”应与“app闪电”继续加深合作。\n",
    "\n",
    "    * 5、“电商”中的贷款客户，收益率水平明显较低，逾期率却不低，在该群体中的贷款收益小，风险大。\n",
    "\n",
    "    * 6、从性别上看，男性群体贷款利率较高，逾期风险较小，相较女性一定程度上是更为优质的客户，但并不明显。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.LCLP数据集分析用户的还款情况\n",
    "基于LCLP 数据，分析用户的还款习惯（提前一次性全部还款 、部分提前还款以及逾期还款）的金额占比。\n",
    "\n",
    "将数据集按借款金额分组，并按还款状态和还款日期分成四种还款情况并进行统计：\n",
    "\n",
    "（1）一次性全部还款：其还款状态标记为‘已提前还清该标全部欠款’；\n",
    "\n",
    "（2）部分提前还款：其还款状态标记为’已正常还款’，并且当期的还款日期早于到期日期；\n",
    "\n",
    "（3）正常还款：其还款状态标记为’已正常还款’，并且当期的还款日期即为到期日期；\n",
    "\n",
    "（4）逾期还款：还款状态标记为‘未还款’，‘已逾期还款’或者‘已部分还款’。\n",
    "\n",
    "用百分堆积柱状图展示在不同年龄段（15 -20 ，20 -25 ，25 -30 ， 30-35 ，35 -40 ，40+ ）,\n",
    "不同性别（ 男、女），不同初始评级（A-F），\n",
    "不同借款类型、不同借款金额（1-1000，1000 -2000，2000-3000，3000+）、不同期数（1-24）的走势。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:46:38.803098Z",
     "start_time": "2020-07-30T13:46:37.062101Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1600898 entries, 0 to 3117188\n",
      "Data columns (total 10 columns):\n",
      "ListingId     1600898 non-null int64\n",
      "期数            1600898 non-null int64\n",
      "还款状态          1600898 non-null int64\n",
      "应还本金          1600898 non-null float64\n",
      "应还利息          1600898 non-null float64\n",
      "剩余本金          1600898 non-null float64\n",
      "剩余利息          1600898 non-null float64\n",
      "到期日期          1600898 non-null object\n",
      "还款日期          1600898 non-null object\n",
      "recorddate    1600898 non-null object\n",
      "dtypes: float64(4), int64(3), object(3)\n",
      "memory usage: 134.4+ MB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(None,\n",
       "                count          mean           std       min         25%  \\\n",
       " ListingId  1600898.0  1.418539e+07  7.002965e+06  126541.0  8841501.00   \n",
       " 期数         1600898.0  4.114305e+00  2.845315e+00       1.0        2.00   \n",
       " 还款状态       1600898.0  1.144276e+00  4.858882e-01       0.0        1.00   \n",
       " 应还本金       1600898.0  5.436048e+02  2.844548e+03       0.0      207.55   \n",
       " 应还利息       1600898.0  5.496813e+01  1.109907e+02       0.0       21.26   \n",
       " 剩余本金       1600898.0  1.428359e+01  2.162337e+02       0.0        0.00   \n",
       " 剩余利息       1600898.0  1.342594e+00  1.230039e+01       0.0        0.00   \n",
       " \n",
       "                    50%          75%          max  \n",
       " ListingId  12825041.00  19173611.00  32227801.00  \n",
       " 期数                3.00         6.00        24.00  \n",
       " 还款状态              1.00         1.00         4.00  \n",
       " 应还本金            356.21       535.14    500000.00  \n",
       " 应还利息             42.30        70.34     18750.00  \n",
       " 剩余本金              0.00         0.00     77348.37  \n",
       " 剩余利息              0.00         0.00      3199.99  )"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除尚未到期的记录\n",
    "LP = LP[LP['到期日期'] <= LP['recorddate']]\n",
    "LP.info(),LP.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:47:31.011191Z",
     "start_time": "2020-07-30T13:47:29.811878Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ListingId</th>\n",
       "      <th>借款金额</th>\n",
       "      <th>借款期限</th>\n",
       "      <th>借款利率</th>\n",
       "      <th>借款成功日期</th>\n",
       "      <th>初始评级</th>\n",
       "      <th>借款类型</th>\n",
       "      <th>是否首标</th>\n",
       "      <th>年龄</th>\n",
       "      <th>性别</th>\n",
       "      <th>...</th>\n",
       "      <th>逾期还款率</th>\n",
       "      <th>期数</th>\n",
       "      <th>还款状态</th>\n",
       "      <th>应还本金</th>\n",
       "      <th>应还利息</th>\n",
       "      <th>剩余本金</th>\n",
       "      <th>剩余利息</th>\n",
       "      <th>到期日期</th>\n",
       "      <th>还款日期</th>\n",
       "      <th>recorddate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>126541</td>\n",
       "      <td>18000</td>\n",
       "      <td>12</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2015-05-04</td>\n",
       "      <td>C</td>\n",
       "      <td>其他</td>\n",
       "      <td>否</td>\n",
       "      <td>35</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>21.917808</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1380.23</td>\n",
       "      <td>270.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-06-04</td>\n",
       "      <td>2015-06-04</td>\n",
       "      <td>2017-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>126541</td>\n",
       "      <td>18000</td>\n",
       "      <td>12</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2015-05-04</td>\n",
       "      <td>C</td>\n",
       "      <td>其他</td>\n",
       "      <td>否</td>\n",
       "      <td>35</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>21.917808</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1400.94</td>\n",
       "      <td>249.29</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-07-04</td>\n",
       "      <td>2015-07-04</td>\n",
       "      <td>2017-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>126541</td>\n",
       "      <td>18000</td>\n",
       "      <td>12</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2015-05-04</td>\n",
       "      <td>C</td>\n",
       "      <td>其他</td>\n",
       "      <td>否</td>\n",
       "      <td>35</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>21.917808</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1421.95</td>\n",
       "      <td>228.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-08-04</td>\n",
       "      <td>2015-08-04</td>\n",
       "      <td>2017-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>126541</td>\n",
       "      <td>18000</td>\n",
       "      <td>12</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2015-05-04</td>\n",
       "      <td>C</td>\n",
       "      <td>其他</td>\n",
       "      <td>否</td>\n",
       "      <td>35</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>21.917808</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1443.28</td>\n",
       "      <td>206.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-09-04</td>\n",
       "      <td>2015-09-04</td>\n",
       "      <td>2017-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>126541</td>\n",
       "      <td>18000</td>\n",
       "      <td>12</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2015-05-04</td>\n",
       "      <td>C</td>\n",
       "      <td>其他</td>\n",
       "      <td>否</td>\n",
       "      <td>35</td>\n",
       "      <td>男</td>\n",
       "      <td>...</td>\n",
       "      <td>21.917808</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1464.93</td>\n",
       "      <td>185.30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015-10-04</td>\n",
       "      <td>2015-10-04</td>\n",
       "      <td>2017-02-22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ListingId   借款金额  借款期限  借款利率      借款成功日期 初始评级 借款类型 是否首标  年龄 性别     ...      \\\n",
       "0     126541  18000    12  18.0  2015-05-04    C   其他    否  35  男     ...       \n",
       "1     126541  18000    12  18.0  2015-05-04    C   其他    否  35  男     ...       \n",
       "2     126541  18000    12  18.0  2015-05-04    C   其他    否  35  男     ...       \n",
       "3     126541  18000    12  18.0  2015-05-04    C   其他    否  35  男     ...       \n",
       "4     126541  18000    12  18.0  2015-05-04    C   其他    否  35  男     ...       \n",
       "\n",
       "       逾期还款率   期数 还款状态     应还本金    应还利息 剩余本金  剩余利息        到期日期        还款日期  \\\n",
       "0  21.917808  1.0  1.0  1380.23  270.00  0.0   0.0  2015-06-04  2015-06-04   \n",
       "1  21.917808  2.0  1.0  1400.94  249.29  0.0   0.0  2015-07-04  2015-07-04   \n",
       "2  21.917808  3.0  1.0  1421.95  228.28  0.0   0.0  2015-08-04  2015-08-04   \n",
       "3  21.917808  4.0  1.0  1443.28  206.95  0.0   0.0  2015-09-04  2015-09-04   \n",
       "4  21.917808  5.0  1.0  1464.93  185.30  0.0   0.0  2015-10-04  2015-10-04   \n",
       "\n",
       "   recorddate  \n",
       "0  2017-02-22  \n",
       "1  2017-02-22  \n",
       "2  2017-02-22  \n",
       "3  2017-02-22  \n",
       "4  2017-02-22  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将LC和LP两个表融合起来\n",
    "LCLP = pd.merge(LC, LP, how='left', on=['ListingId'])\n",
    "LCLP.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:48:10.517259Z",
     "start_time": "2020-07-30T13:48:06.324643Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1023959 entries, 0 to 1025670\n",
      "Data columns (total 31 columns):\n",
      "ListingId     1023959 non-null int64\n",
      "借款金额          1023959 non-null int64\n",
      "借款期限          1023959 non-null int64\n",
      "借款利率          1023959 non-null float64\n",
      "借款成功日期        1023959 non-null object\n",
      "初始评级          1023959 non-null object\n",
      "借款类型          1023959 non-null object\n",
      "是否首标          1023959 non-null object\n",
      "年龄            1023959 non-null int64\n",
      "性别            1023959 non-null object\n",
      "手机认证          1023959 non-null object\n",
      "户口认证          1023959 non-null object\n",
      "视频认证          1023959 non-null object\n",
      "学历认证          1023959 non-null object\n",
      "征信认证          1023959 non-null object\n",
      "淘宝认证          1023959 non-null object\n",
      "历史成功借款次数      1023959 non-null int64\n",
      "历史成功借款金额      1023959 non-null float64\n",
      "总待还本金         1023959 non-null float64\n",
      "历史正常还款期数      1023959 non-null int64\n",
      "历史逾期还款期数      1023959 non-null int64\n",
      "逾期还款率         1023959 non-null float64\n",
      "期数            1023959 non-null float64\n",
      "还款状态          1023959 non-null float64\n",
      "应还本金          1023959 non-null float64\n",
      "应还利息          1023959 non-null float64\n",
      "剩余本金          1023959 non-null float64\n",
      "剩余利息          1023959 non-null float64\n",
      "到期日期          1023959 non-null object\n",
      "还款日期          1023959 non-null object\n",
      "recorddate    1023959 non-null object\n",
      "dtypes: float64(10), int64(7), object(14)\n",
      "memory usage: 250.0+ MB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(None,\n",
       "           ListingId          借款金额          借款期限          借款利率            年龄  \\\n",
       " count  1.023959e+06  1.023959e+06  1.023959e+06  1.023959e+06  1.023959e+06   \n",
       " mean   1.555568e+07  4.260340e+03  1.018629e+01  2.034064e+01  2.929710e+01   \n",
       " std    7.135938e+06  1.184931e+04  2.833507e+00  1.655421e+00  6.524736e+00   \n",
       " min    1.265410e+05  1.000000e+02  1.000000e+00  6.500000e+00  1.800000e+01   \n",
       " 25%    1.002527e+07  2.000000e+03  6.000000e+00  2.000000e+01  2.500000e+01   \n",
       " 50%    1.511169e+07  3.041000e+03  1.200000e+01  2.000000e+01  2.800000e+01   \n",
       " 75%    2.111501e+07  4.553000e+03  1.200000e+01  2.200000e+01  3.300000e+01   \n",
       " max    3.222780e+07  5.000000e+05  2.400000e+01  2.400000e+01  5.600000e+01   \n",
       " \n",
       "            历史成功借款次数      历史成功借款金额         总待还本金      历史正常还款期数      历史逾期还款期数  \\\n",
       " count  1.023959e+06  1.023959e+06  1.023959e+06  1.023959e+06  1.023959e+06   \n",
       " mean   3.014310e+00  1.198434e+04  4.808516e+03  1.274921e+01  5.755729e-01   \n",
       " std    3.049200e+00  4.356321e+04  9.220797e+03  1.560610e+01  1.766335e+00   \n",
       " min    1.000000e+00  1.000000e+02  0.000000e+00  0.000000e+00  0.000000e+00   \n",
       " 25%    1.000000e+00  3.670000e+03  1.877720e+03  4.000000e+00  0.000000e+00   \n",
       " 50%    2.000000e+00  7.000000e+03  3.734560e+03  8.000000e+00  0.000000e+00   \n",
       " 75%    4.000000e+00  1.253700e+04  6.077980e+03  1.600000e+01  0.000000e+00   \n",
       " max    6.490000e+02  7.405926e+06  1.172653e+06  2.507000e+03  6.000000e+01   \n",
       " \n",
       "               逾期还款率            期数          还款状态          应还本金          应还利息  \\\n",
       " count  1.023959e+06  1.023959e+06  1.023959e+06  1.023959e+06  1.023959e+06   \n",
       " mean   4.133961e+00  3.716038e+00  1.135856e+00  5.270704e+02  4.955353e+01   \n",
       " std    1.116971e+01  2.601770e+00  4.770325e-01  2.849558e+03  1.138766e+02   \n",
       " min    0.000000e+00  1.000000e+00  0.000000e+00  7.520000e+00  0.000000e+00   \n",
       " 25%    0.000000e+00  2.000000e+00  1.000000e+00  1.746400e+02  1.754000e+01   \n",
       " 50%    0.000000e+00  3.000000e+00  1.000000e+00  2.969400e+02  3.600000e+01   \n",
       " 75%    0.000000e+00  5.000000e+00  1.000000e+00  4.981700e+02  5.855000e+01   \n",
       " max    1.000000e+02  2.300000e+01  4.000000e+00  5.000000e+05  1.750000e+04   \n",
       " \n",
       "                剩余本金          剩余利息  \n",
       " count  1.023959e+06  1.023959e+06  \n",
       " mean   1.112097e+01  1.004733e+00  \n",
       " std    1.896729e+02  1.091655e+01  \n",
       " min    0.000000e+00  0.000000e+00  \n",
       " 25%    0.000000e+00  0.000000e+00  \n",
       " 50%    0.000000e+00  0.000000e+00  \n",
       " 75%    0.000000e+00  0.000000e+00  \n",
       " max    6.531642e+04  3.199990e+03  )"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除数据不全的记录\n",
    "LCLP = LCLP.dropna(how='any')\n",
    "LCLP.info(),LCLP.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:49:11.278353Z",
     "start_time": "2020-07-30T13:49:11.264360Z"
    }
   },
   "outputs": [],
   "source": [
    "#定义用户还款习惯分析可视化函数\n",
    "def repayhabit(group,num,idx,xlabel,color):\n",
    "    # 一次性全部还款\n",
    "    onetime = []\n",
    "    for a in group:\n",
    "        ot = a.loc[a['还款状态'] == 3]['应还本金'].sum(\n",
    "            ) + a.loc[a['还款状态'] == 3]['应还利息'].sum()\n",
    "        onetime.append(ot)\n",
    "    # 部分提前还款\n",
    "    partial = []\n",
    "    for a in group:\n",
    "        pa = a.loc[(a['还款状态'] == 1) & (a['还款日期'] < a['到期日期'])]['应还本金'].sum(\n",
    "            ) + a.loc[(a['还款状态'] == 1) & (a['还款日期'] < a['到期日期'])]['应还利息'].sum()\n",
    "        partial.append(pa)\n",
    "    # 逾期还款\n",
    "    pastdue = []\n",
    "    for a in group:\n",
    "        pas = a.loc[(a['还款状态'] == 2) | (a['还款状态'] == 4)|(a['还款状态'] == 0)]['应还本金'].sum() + \\\n",
    "            a.loc[(a['还款状态'] == 2) | (a['还款状态'] == 4)|(a['还款状态'] == 0)]['应还利息'].sum()\n",
    "        pastdue.append(pas)\n",
    "    # 正常还款\n",
    "    normal = []\n",
    "    for a in group:\n",
    "        nm = a.loc[(a['还款状态'] == 1) & (a['还款日期'] == a['到期日期'])]['应还本金'].sum(\n",
    "        ) + a.loc[(a['还款状态'] == 1) & (a['还款日期'] == a['到期日期'])]['应还利息'].sum()\n",
    "        normal.append(nm)\n",
    "    \n",
    "    tot = []\n",
    "    for i in range(num):\n",
    "        t = onetime[i]+partial[i]+pastdue[i]+normal[i]\n",
    "        tot.append(t)\n",
    "\n",
    "    print(tot)\n",
    "\n",
    "    temp = []\n",
    "    for i in range(num):\n",
    "        tp = (100 * onetime[i] / tot[i], 100 * partial[i] / tot[i],\n",
    "                100 * normal[i] / tot[i], 100 * pastdue[i] / tot[i])\n",
    "        temp.append(tp)\n",
    "        \n",
    "    df = pd.DataFrame(temp)\n",
    "    df.index = idx\n",
    "    df.columns = ('提前一次性', '部分提前', '正常', '逾期')\n",
    "    print(df)\n",
    "\n",
    "    df.plot(kind='bar', colormap=color, stacked=True)\n",
    "    plt.ylabel('还款金额')\n",
    "    plt.xlabel(xlabel)\n",
    "    plt.legend(loc='best')\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:50:20.756675Z",
     "start_time": "2020-07-30T13:50:18.677196Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[28456834.85, 69903191.44000001, 99595369.9, 72161874.03, 51083566.29000001, 269236628.2506]\n",
      "               提前一次性       部分提前         正常         逾期\n",
      "0-2000     10.204426  60.954742  16.233811  12.607020\n",
      "2000-3000  10.208217  54.959603  20.400835  14.431346\n",
      "3000-4000  14.874141  50.961604  21.902815  12.261440\n",
      "4000-5000  14.678874  50.698304  22.775784  11.847038\n",
      "5000-6000  15.703463  50.299053  23.239861  10.757622\n",
      "6000+      11.688029  39.376116  39.790049   9.145806\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分析不同借款金额用户的还款情况\n",
    "amountA = LCLP.loc[(LCLP['借款金额'] > 0) & (LCLP['借款金额'] < 2000)]\n",
    "amountB = LCLP.loc[(LCLP['借款金额'] >= 2000) & (LCLP['借款金额'] < 3000)]\n",
    "amountC = LCLP.loc[(LCLP['借款金额'] >= 3000) & (LCLP['借款金额'] < 4000)]\n",
    "amountD = LCLP.loc[(LCLP['借款金额'] >= 4000) & (LCLP['借款金额'] < 5000)]\n",
    "amountE = LCLP.loc[(LCLP['借款金额'] >= 5000) & (LCLP['借款金额'] < 6000)]\n",
    "amountF = LCLP.loc[(LCLP['借款金额'] >= 6000)]\n",
    "amountgroup = [amountA, amountB, amountC, amountD,amountE,amountF]\n",
    "\n",
    "repayhabit(amountgroup,6,amount_idx,'借款金额','Greys_r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:52:25.130223Z",
     "start_time": "2020-07-30T13:52:25.119231Z"
    }
   },
   "source": [
    "* 在根据借款金额分组中，得到结果如下：\n",
    "\n",
    "* A组（0-2000）：总金额2.85千万。（1）一次性全部还款：占比 10.20%；（2）部分提前还款：占比60.95%；（3）正常还款：占比 16.23%； （4）逾期还款：占比 12.61%。\n",
    "\n",
    "* B组（2000-3000）：总金额 7千万。（1）一次性全部还款：占比 10.21%；（2）部分提前还款：占比54.96%；（3）正常还款：占比 20.40%； （4）逾期还款：占比 14.43%。\n",
    "\n",
    "* C组（3000-4000）：总金额 10千万。（1）一次性全部还款：占比 14.87%；（2）部分提前还款：占比50.96%；（3）正常还款：占比 21.90%； （4）逾期还款：占比 12.26%。\n",
    "\n",
    "* D组（4000-5000）：总金额 7.22千万。（1）一次性全部还：占比 14.68%；（2）部分提前还款：占比50.70%；（3）正常还款：占比 22.78%； （4）逾期还款：占比 11.85%。\n",
    "\n",
    "* E组（5000-6000）：总金额 5.11千万。（1）一次性全部还款：占比 15.70%；（2）部分提前还款：占比50.30%；（3）正常还款：占比 23.24%； （4）逾期还款：占比 10.76%。\n",
    "\n",
    "* F组（6000+）：总金额 26.92千万。（1）一次性全部还款：占比 11.69%；（2）部分提前还款：占比39.38%；（3）正常还款：占比 39.79%； （4）逾期还款：占比 9.15%。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:53:16.550195Z",
     "start_time": "2020-07-30T13:53:16.530196Z"
    }
   },
   "source": [
    "* 从对借款金额分组的统计结果以及上图结果中可以看出：\n",
    "\n",
    "* （1）借款总额6000元以上最多，3000-4000其次，说明3000-4000元的借款金额是最多的。\n",
    "\n",
    "* （2）逾期风险在各金额组表现比较平均，其中2000-3000最大，6000+最小。\n",
    "\n",
    "* （3）随着标的金额增加，部分提前还款的总金额比例在减少，正常还款的总金额比例在增加。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:54:20.084267Z",
     "start_time": "2020-07-30T13:54:18.045439Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1325708.5400000003, 85978811.91999999, 203407279.9106, 149443150.8962, 79947743.0043, 70334770.4895]\n",
      "           提前一次性       部分提前         正常         逾期\n",
      "15-20  10.441107  62.896452  13.114767  13.547674\n",
      "20-25  13.428313  53.199581  20.048697  13.323409\n",
      "25-30  14.002901  47.665900  26.687108  11.644091\n",
      "30-35  12.363756  43.932650  33.824134   9.879460\n",
      "35-40  10.805522  44.388718  34.672769  10.132990\n",
      "40+    10.882495  42.854777  37.205296   9.057432\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分析不同年龄段用户的还款情况\n",
    "ageA = LCLP.loc[(LCLP['年龄'] >= 15) & (LCLP['年龄'] < 20)]\n",
    "ageB = LCLP.loc[(LCLP['年龄'] >= 20) & (LCLP['年龄'] < 25)]\n",
    "ageC = LCLP.loc[(LCLP['年龄'] >= 25) & (LCLP['年龄'] < 30)]\n",
    "ageD = LCLP.loc[(LCLP['年龄'] >= 30) & (LCLP['年龄'] < 35)]\n",
    "ageE = LCLP.loc[(LCLP['年龄'] >= 35) & (LCLP['年龄'] < 40)]\n",
    "ageF = LCLP.loc[LCLP['年龄'] >= 40]\n",
    "agegroup = [ageA, ageB, ageC, ageD, ageE, ageF]\n",
    "\n",
    "repayhabit(agegroup,6,age_idx,'年龄','Reds_r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:55:17.821074Z",
     "start_time": "2020-07-30T13:55:17.807064Z"
    }
   },
   "source": [
    "* 在年龄分组中，得到结果如下：\n",
    "\n",
    "* A组（15-20岁）：总金额0.13千万。（1）一次性全部还款：占比 10.44%；（2）部分提前还款：占比62.90%；（3）正常还款：占比 13.11%； （4）逾期还款：占比 13.55%。\n",
    "\n",
    "* B组（20-25岁）：总金额 8.60千万。（1）一次性全部还款：占比 13.43%；（2）部分提前还款：占比53.2%；（3）正常还款：占比 20.05%； （4）逾期还款：占比 13.32%。\n",
    "\n",
    "* C组（25-30岁）：总金额 20.34千万。（1）一次性全部还款：占比 14.00%；（2）部分提前还款：占比47.67%；（3）正常还款：占比 26.69%； （4）逾期还款：占比 11.64%。\n",
    "\n",
    "* D组（30-35岁）：总金额 14.94千万。（1）一次性全部还款：占比 12.36%；（2）部分提前还款：占比43.92%；（3）正常还款：占比 33.82%； （4）逾期还款：占比 9.88%。\n",
    "\n",
    "* E组（35-40岁）：总金额 8.00千万。（1）一次性全部还款：占比 10.81%；（2）部分提前还款：占比44.39%；（3）正常还款：占比 34.67%； （4）逾期还款：占比 10.13%。\n",
    "\n",
    "* F组（40岁+）：总金额 7.03千万。（1）一次性全部还款：占比 10.88%；（2）部分提前还款：占比42.85%；（3）正常还款：占比 37.21%； （4）逾期还款：占比 9.06%。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 从对年龄分组的统计结果以及上图结果中可以看出：\n",
    "\n",
    "    * （1）拍拍贷的客户群体中25-30岁年龄组的贷款金额最高，15-20岁最低；\n",
    "\n",
    "    * （2）各年龄组的还款习惯大体一致，从金额上来说，部分提前还款和正常还款是最常用的方式；\n",
    "\n",
    "    * （3）逾期还款风险最高的年龄组为15-20岁组；\n",
    "\n",
    "    * （4）25-30岁年龄组一次性提前还款的金额占比最高。\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:56:14.682143Z",
     "start_time": "2020-07-30T13:56:12.611336Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[431899402.1953, 158538062.5653]\n",
      "       提前一次性       部分提前         正常         逾期\n",
      "男  13.159444  45.775236  30.093425  10.971895\n",
      "女  11.417458  48.638828  29.114713  10.829001\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分析不同性别用户的还款情况\n",
    "male = LCLP.loc[LCLP['性别'] == \"男\"]\n",
    "female = LCLP.loc[LCLP['性别'] == \"女\"]\n",
    "sexgroup = (male,female)\n",
    "\n",
    "repayhabit(sexgroup,2,sex_idx,'性别','Greens_r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 在男女性别组中，得到结果如下：\n",
    "\n",
    "* 男性：总还款金额 43.19千万。（1）一次性全部还款占比 13.16%；（2）部分提前还款占比45.78%；（3）正常还款占比 30.09%； （4）逾期还款占比10.97%。\n",
    "\n",
    "* 女性：总还款金额 15.85千万。（1）一次性全部还款占比 11.42%；（2）部分提前还款占比48.64%；（3）正常还款占比29.11%； （4）逾期还款占比10.83%。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:57:18.510511Z",
     "start_time": "2020-07-30T13:57:18.503521Z"
    }
   },
   "source": [
    "* 从对男女性别组的统计结果以及上图结果中可以看出：\n",
    "\n",
    "    * （1）拍拍贷男性客户的贷款金额约为女性客户的2.7倍；\n",
    "\n",
    "    * （2）男性及女性的还款习惯大体上比较一致，从金额上来说，部分提前还款>正常还款>一次性提前还款>逾期还款；\n",
    "\n",
    "    * （3）男性客户一次性提前还款的金额占比较女性为高；\n",
    "\n",
    "    * （4）女性逾期还款的风险略低于男性；\n",
    "\n",
    "    * （5）女性部分提前还款的金额占比略大于男性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:57:48.837004Z",
     "start_time": "2020-07-30T13:57:46.012292Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[24260113.047399998, 129789781.91, 292672443.2151, 131419854.39039999, 10771732.247699998, 1523539.95]\n",
      "       提前一次性       部分提前         正常         逾期\n",
      "A  10.951641  42.540019  39.727788   6.780552\n",
      "B   7.686131  37.447042  47.651688   7.215139\n",
      "C  14.192953  49.919494  24.995052  10.892502\n",
      "D  14.592841  49.269359  21.846049  14.291750\n",
      "E  13.213394  40.965391  22.906776  22.914440\n",
      "F  10.752586  41.241621  20.679682  27.326111\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分析不同初始评级客户的还款情况\n",
    "levelgroup = []\n",
    "for i in level_idx:\n",
    "    l = LCLP[(LCLP['初始评级'] == i)]\n",
    "    levelgroup.append(l)\n",
    "    \n",
    "repayhabit(levelgroup,6,level_idx,'初始评级','Blues_r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:58:24.774169Z",
     "start_time": "2020-07-30T13:58:24.762178Z"
    }
   },
   "source": [
    "* 在初始评级分组中，得到结果如下：\n",
    "\n",
    "* A级：总金额2.43千万。（1）一次性全部还款：占比 10.95%；（2）部分提前还款：占比42.54%；（3）正常还款：占比 39.73%； （4）逾期还款：占比 6.78%。\n",
    "\n",
    "* B级：总金额 12.98千万。（1）一次性全部还款：占比 7.68%；（2）部分提前还款：占比37.45%；（3）正常还款：占比 47.65%； （4）逾期还款：占比 7.22%。\n",
    "\n",
    "* C级：总金额 29.27千万。（1）一次性全部还款：占比 14.19%；（2）部分提前还款：占比49.92%；（3）正常还款：占比 25.00%； （4）逾期还款：占比 10.89%。\n",
    "\n",
    "* D级：总金额 13.14千万。（1）一次性全部还款：占比 14.59%；（2）部分提前还款：占比49.27%；（3）正常还款：占比 21.85%； （4）逾期还款：占比 14.29%。\n",
    "\n",
    "* E级：总金额 1.08千万。（1）一次性全部还款：占比 13.21%；（2）部分提前还款：占比40.97%；（3）正常还款：占比 22.91%； （4）逾期还款：占比 22.91%。\n",
    "\n",
    "* F级：总金额 0.15千万。（1）一次性全部还款：占比 10.75%；（2）部分提前还款：占比41.24%；（3）正常还款：占比 20.68%； （4）逾期还款：占比 27.33%。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 从对初始评级分组的统计结果可以看出：\n",
    "\n",
    "    * （1）B级客户借款总额最多，占到了大约50%的金额。B、C、D级客户是借款的主力军。\n",
    "\n",
    "    * （2）提前一次性还款的占比相对比较平均，其中D级最大为14.59%。\n",
    "\n",
    "    * （3）逾期风险随着级别而呈总体增加趋势，F级客户的逾期占比达到了27.33%。\n",
    "\n",
    "    * （4）部分提前和正常还款还是占到了大多数。\n",
    "\n",
    "    * （5）总的来说，初始评级具有重要的参考意义。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T13:59:38.625236Z",
     "start_time": "2020-07-30T13:59:36.102095Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[85700890.47, 74452365.96, 234675993.36, 195608214.9706]\n",
      "           提前一次性       部分提前         正常         逾期\n",
      "电商      4.218635  26.927505  62.071671   6.782188\n",
      "APP闪电   8.959958  61.125398  18.677700  11.236944\n",
      "普通     17.162002  45.092948  26.095824  11.649226\n",
      "其他     12.461221  51.329790  24.430785  11.778204\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#  分析不同借款类型客户的还款情况\n",
    "kindgroup = []\n",
    "for i in kind_idx:\n",
    "    l = LCLP[(LCLP['借款类型'] == i)]\n",
    "    kindgroup.append(l)\n",
    "    \n",
    "repayhabit(kindgroup,4,kind_idx,'借款类型','Reds_r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 在借款类型分组中，得到结果如下：\n",
    "\n",
    "* 电商：总金额8.57千万。（1）一次性全部还款：占比 4.22%；（2）部分提前还款：占比26.93%；（3）正常还款：占比 62.07%； （4）逾期还款：占比 6.78%。\n",
    "\n",
    "*  APP闪电：总金额 7.45千万。（1）一次性全部还款：占比 8.96%；（2）部分提前还款：占比61.13%；（3）正常还款：占比 18.68%； （4）逾期还款：占比11.24%。\n",
    "\n",
    "* 普通：总金额 23.47千万。（1）一次性全部还款：占比 17.16%；（2）部分提前还款：占比45.09%；（3）正常还款：占比 26.10%； （4）逾期还款：占比 11.65%。\n",
    "\n",
    "* 其他：总金额 19.56千万。（1）一次性全部还款：占比 12.46%；（2）部分提前还款：占比51.33%；（3）正常还款：占比 24.43%； （4）逾期还款：占比 11.78%。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 从对借款类型分组的统计结果可以看出：\n",
    "\n",
    "    * （1）普通借款类型的借款金额总数最大，其次是其他，电商和APP闪电差不多。\n",
    "\n",
    "    * （2）逾期风险电商最低，为6.78%。其他三种类型差不多。\n",
    "    \n",
    "    * （3）部分提前和正常还款还是占到了大多数。值得注意的是除了电商，其他三种类型的部分提前还款都占比很大。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:01:23.049123Z",
     "start_time": "2020-07-30T14:01:20.209250Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[135981578.1922, 108408463.47999999, 93715601.03, 75294688.9507, 60648276.0339, 47917912.09030001, 19092666.1202, 15699880.5325, 12331986.870000001, 9339947.0008, 6687098.62, 4416541.7700000005, 301461.70999999996, 169327.15999999997, 143667.96000000002, 83483.42, 69138.15, 50308.28, 36507.18, 19895.030000000002, 17235.37, 7340.29, 4459.52, 0.0]\n",
      "        提前一次性       部分提前         正常         逾期\n",
      "1   11.445900  47.586534  33.902811   7.064756\n",
      "2   12.167250  50.653062  28.728319   8.451370\n",
      "3   15.843928  46.505031  28.396910   9.254131\n",
      "4   14.029461  44.266042  30.340452  11.364045\n",
      "5   12.805724  44.175306  30.414081  12.604889\n",
      "6    9.611442  44.158815  31.276022  14.953720\n",
      "7   15.717427  44.974685  22.785384  16.522504\n",
      "8   14.343482  44.269646  23.244959  18.141913\n",
      "9   11.168077  44.718088  23.378983  20.734852\n",
      "10  10.209341  44.175032  23.368664  22.246963\n",
      "11   7.335732  43.147448  24.866896  24.649924\n",
      "12   3.498742  46.299654  23.112021  27.089583\n",
      "13  40.902773  19.437918  24.870807  14.788502\n",
      "14  11.418682  31.512434  29.150120  27.918764\n",
      "15  16.023385  28.828836  24.818436  30.329344\n",
      "16   0.000000  29.785926  27.199592  43.014481\n",
      "17   0.000000  17.118002  31.699792  51.182205\n",
      "18   0.000000  20.567111  30.283941  49.148947\n",
      "19   0.000000  21.394969  23.491982  55.113049\n",
      "20   0.000000  23.093557  35.159937  41.746507\n",
      "21  22.619068  16.714292  34.597227  26.069414\n",
      "22   0.000000  72.794535  27.205465   0.000000\n",
      "23   0.000000   0.000000  83.207610  16.792390\n",
      "24        NaN        NaN        NaN        NaN\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:36: RuntimeWarning: invalid value encountered in double_scalars\n",
      "D:\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:37: RuntimeWarning: invalid value encountered in double_scalars\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "term_idx = ('1','2','3','4','5','6','7','8','9','10','11','12','13','14','15','16','17','18','19','20','21','22','23','24')\n",
    "termgroup = []\n",
    "for i in range(1,25):\n",
    "    term = LCLP.loc[(LCLP['期数'] == i)]\n",
    "    termgroup.append(term)\n",
    "\n",
    "repayhabit(termgroup,24,term_idx,'期数','Reds_r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:02:32.497872Z",
     "start_time": "2020-07-30T14:02:32.478906Z"
    }
   },
   "source": [
    "从对期数分组的统计结果可以看出：\n",
    "\n",
    "（1）借款金额是随着期数增加呈现出下降的趋势。\n",
    "\n",
    "（2）不同的还款行为在不同的借款期限下的表现差异比较大，部分提前还款和正常还款是最常用的方式；\n",
    "\n",
    "（3）逾期风险随着借款期限变长而呈总体增加趋势，期限为20个月的逾期金额占比为最高，达到了57.30%；\n",
    "\n",
    "（4）期限为13个月的提前一次性还款占比最高，达到了16.77%。\n",
    "\n",
    "（5）借款期限太长的样本数量太少，不能排除偶然性。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:02:47.613234Z",
     "start_time": "2020-07-30T14:02:47.605240Z"
    }
   },
   "source": [
    "# 3.计算金额催收回款率（催收回本金/所有逾期本金）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在不同等级（A-F）、不同借款期数（1-24）和不同借款金额（0-2000，2000-3000，3000-4000，4000-5000，5000-6000，6000+）等，随逾期天数增加而呈现的走势。\n",
    "\n",
    "1）x轴为逾期天数，y轴为金额催收回款率，不同参数对应不同曲线；\n",
    "\n",
    "2）催收回款的定义为逾期90天之内的逾期还款。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:03:47.463879Z",
     "start_time": "2020-07-30T14:03:42.454955Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime,timedelta\n",
    "\n",
    "#LCLP.info()\n",
    "LCLP['recorddate'] = pd.to_datetime(LCLP['recorddate'])\n",
    "LCLP['到期日期'] = pd.to_datetime(LCLP['到期日期'])\n",
    "LCLP['还款日期'] = pd.to_datetime(LCLP['还款日期'], errors='coerce')\n",
    "LCLP['lateday'] = LCLP['还款日期']-LCLP['到期日期']\n",
    "\n",
    "depay = LCLP[LCLP['lateday']>timedelta(days=0)]\n",
    "\n",
    "#不同等级（A-F）随逾期天数催收还款率的走势\n",
    "df = depay.groupby(['初始评级','lateday'])['应还本金'].sum()\n",
    "df1 = df.to_frame().pivot_table(index='lateday',columns = '初始评级', values ='应还本金')\n",
    "tmp = df1.fillna(0)\n",
    "df2 = depay.groupby(['初始评级'])['应还本金'].sum()\n",
    "tmp_1 = tmp[tmp.index <= timedelta(days=90)]\n",
    "tmp_1 = tmp_1/df2\n",
    "\n",
    "plt.figure(figsize=(15, 8))\n",
    "for i in range(6):\n",
    "    plt.subplot(2,3,i+1)\n",
    "    plt.plot(range(90),tmp_1[level_idx[i]])\n",
    "    plt.title(level_idx[i])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:04:21.323581Z",
     "start_time": "2020-07-30T14:04:21.318587Z"
    }
   },
   "source": [
    "不同等级（A-F）随逾期天数催收还款率的走势大致相同，也就是大部分人都在逾期十天之内还款，说明他们有可能忘记还款；特别是在4、5天的还款的人数和金额最多"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:04:39.852444Z",
     "start_time": "2020-07-30T14:04:38.018925Z"
    }
   },
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "22.0",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   3077\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3078\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3079\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Float64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Float64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 22.0",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-181-c409c70d8864>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     12\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m24\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     13\u001b[0m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m6\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 14\u001b[1;33m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m90\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mtmp_1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     15\u001b[0m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mxticks\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m30\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m60\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m90\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     16\u001b[0m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   2686\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2687\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2688\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2689\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2690\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   2693\u001b[0m         \u001b[1;31m# get column\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2694\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2695\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2696\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2697\u001b[0m         \u001b[1;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[1;34m(self, item)\u001b[0m\n\u001b[0;32m   2487\u001b[0m         \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2488\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2489\u001b[1;33m             \u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2490\u001b[0m             \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2491\u001b[0m             \u001b[0mcache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mres\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\internals.py\u001b[0m in \u001b[0;36mget\u001b[1;34m(self, item, fastpath)\u001b[0m\n\u001b[0;32m   4113\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4114\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misna\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 4115\u001b[1;33m                 \u001b[0mloc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   4116\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4117\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0misna\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\indexes\\numeric.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m    417\u001b[0m             \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    418\u001b[0m         return super(Float64Index, self).get_loc(key, method=method,\n\u001b[1;32m--> 419\u001b[1;33m                                                  tolerance=tolerance)\n\u001b[0m\u001b[0;32m    420\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    421\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0mcache_readonly\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mget_loc\u001b[1;34m(self, key, method, tolerance)\u001b[0m\n\u001b[0;32m   3078\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3079\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3080\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3081\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3082\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Float64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mpandas\\_libs\\hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.Float64HashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 22.0"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x864 with 22 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#不同借款期数（1-24）随逾期天数催收还款率的走势\n",
    "#由于期数为24的项目不存在逾期还款的现象，所以只对1-23进行分析\n",
    "\n",
    "df = depay.groupby(['期数','lateday'])['应还本金'].sum()\n",
    "df1 = df.to_frame().pivot_table(index='lateday',columns = '期数', values ='应还本金')\n",
    "tmp = df1.fillna(0)\n",
    "df2 = depay.groupby(['期数'])['应还本金'].sum()\n",
    "tmp_1 = tmp[tmp.index <= timedelta(days=90)]\n",
    "tmp_1 = tmp_1/df2\n",
    "\n",
    "plt.figure(figsize=(15, 12))\n",
    "for i in range(1,24):\n",
    "    plt.subplot(4,6,i)\n",
    "    plt.plot(range(90),tmp_1[i])\n",
    "    plt.xticks([0,30,60,90])\n",
    "    plt.title(str(i))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "不同借款期数（1-24）的金额收回款率随逾期天数的趋势没有明显的规律。在12期及之前大部分人都在逾期十天之内还款，特别是在4、5天的还款的人数和金额最多。 但是13之后呈现出10天之后回款率的依然很大。也有可能是因为数据量导致异常值凸显，但是也说明了借款期数长的回款率不够稳定。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:06:24.687182Z",
     "start_time": "2020-07-30T14:06:19.632685Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:16: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  app.launch_new_instance()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#不同借款金额随逾期天数催收还款率的走势\n",
    "def function(a):\n",
    "    if a>0 and a<2000:\n",
    "        return '0-2000'\n",
    "    elif a>=2000 and a<3000:\n",
    "        return '2000-3000'\n",
    "    elif a>=3000 and a<4000:\n",
    "        return '3000-4000'\n",
    "    elif a>=4000 and a<5000:\n",
    "        return '4000-5000'\n",
    "    elif a>=5000 and a<6000:\n",
    "        return '5000-6000'\n",
    "    else:\n",
    "        return '6000+'\n",
    "\n",
    "depay['金额类型'] = depay.apply(lambda x:function(x['借款金额']),axis=1)\n",
    "\n",
    "df = depay.groupby(['金额类型','lateday'])['应还本金'].sum().copy()\n",
    "df1 = df.to_frame().pivot_table(index='lateday',columns = '金额类型', values ='应还本金')\n",
    "tmp = df1.fillna(0)\n",
    "df2 = depay.groupby(['金额类型'])['应还本金'].sum()\n",
    "tmp_1 = tmp[tmp.index <= timedelta(days=90)]\n",
    "tmp_1 = tmp_1/df2\n",
    "\n",
    "plt.figure(figsize=(15, 8))\n",
    "for i in range(6):\n",
    "    plt.subplot(2,3,i+1)\n",
    "    plt.plot(range(90),tmp_1[amount_idx[i]])\n",
    "    plt.xticks([0,30,60,90])\n",
    "    plt.title(amount_idx[i])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4.累积收益曲线\n",
    "LCIS数据提供了该客户投资的从2015年1月1日起成交的所有标。包括投标记录和还款状况。请计算并画出该投资人从2016年9月开始到2017年2月，每月月底的累计收益曲线。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-07-30T14:08:08.076973Z",
     "start_time": "2020-07-30T14:08:02.098375Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime,timedelta\n",
    "LCIS = pd.read_csv(\"ppdai2017/LCIS.csv\",encoding = 'utf-8')\n",
    "\n",
    "# 计算从2016年9月至2017年2月所有的利息\n",
    "def getinterest(df):\n",
    "    df_1 = df[['ListingId','标当前状态','上次还款日期','上次还款利息']]\n",
    "    df_1 = df_1[(df_1['标当前状态'] =='正常还款中') | (df_1['标当前状态'] =='已还清')]\n",
    "    df_1['上次还款日期'] = df_1['上次还款日期'].where(df_1['上次还款日期'].notnull(),'2016/08/31')\n",
    "    df_1['上次还款日期'] = pd.to_datetime(df_1['上次还款日期'], errors='coerce')\n",
    "    df_1 = df_1[df_1['上次还款日期']>='2016-09-01'].drop_duplicates()\n",
    "    df_1_1 = df_1.groupby(['上次还款日期'])['上次还款利息'].sum().to_frame().reset_index()\n",
    "    return df_1_1\n",
    "\n",
    "# 计算从2016年9月至2017年2月所有的亏损\n",
    "def getloss(df):    \n",
    "    df_2 = df[['ListingId', '待还本金', '标当前状态', '上次还款日期', '下次计划还款日期', 'recorddate']]\n",
    "    df_2 = df_2[(df_2['标当前状态']=='逾期中')]\n",
    "    df_2['下次计划还款日期'] = pd.to_datetime(df_2['下次计划还款日期'], errors='coerce')\n",
    "    df_2['recorddate'] = pd.to_datetime(df_2['recorddate'], errors='coerce')\n",
    "    \n",
    "    # 往回看90天到2016-06-03\n",
    "    df_2 = df_2[df_2['下次计划还款日期']>='2016-06-03']\n",
    "    df_2['delay'] = df_2.apply(lambda x: (x['recorddate'] - x['下次计划还款日期']).days, axis = 1)\n",
    "    df_2_1 = df_2[df_2['delay']>=90].sort_values(['ListingId','delay'])\n",
    "    df_2_1['date'] = df_2['下次计划还款日期'] + timedelta(days=90)\n",
    "    df_2_2 = df_2_1.loc[df_2_1.sort_values('recorddate').iloc[:,0].drop_duplicates().index]\n",
    "    df_2_2 = df_2_2[['date','待还本金']].groupby(['date'])['待还本金'].sum().to_frame().reset_index()\n",
    "    return df_2_2\n",
    "\n",
    "# merge gain and loss\n",
    "def profit(df):\n",
    "    df_1_1 = getinterest(df)\n",
    "    df_2_2 = getloss(df)\n",
    "    df_now = pd.merge(df_1_1,df_2_2, how = 'left', left_on = '上次还款日期', right_on = 'date')    \n",
    "    df_now['待还本金'] = df_now['待还本金'].where(df_now['待还本金'].notnull(),0)\n",
    "    df_now['差别'] = df_now['上次还款利息'] - df_now['待还本金']\n",
    "    return df_now\n",
    "\n",
    "def draw(df):\n",
    "    df_now = profit(df)\n",
    "    plt.plot(df_now['上次还款日期'], np.cumsum(df_now['差别']), label=\"利息\")\n",
    "    plt.title('累积收益曲线')\n",
    "    plt.xlabel('时间')\n",
    "    plt.ylabel('收益金额')\n",
    "    plt.show()\n",
    "\n",
    "draw(LCIS)"
   ]
  }
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